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2014 | OriginalPaper | Buchkapitel

A Survey of Evaluation in Music Genre Recognition

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Abstract

Much work is focused upon music genre recognition (MGR) from audio recordings, symbolic data, and other modalities. While reviews have been written of some of this work before, no survey has been made of the approaches to evaluating approaches to MGR. This paper compiles a bibliography of work in MGR, and analyzes three aspects of evaluation: experimental designs, datasets, and figures of merit.

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Fußnoten
1
Numbers in parentheses are the number of works in the references.
 
Literatur
1.
Zurück zum Zitat Abeßer, J., Dittmar, C., Großmann, H.: Automatic genre and artist classification by analyzing improvised solo parts from musical recordings. In: Proceedings of the Audio Mostly Conference, Piteå, Sweden, pp. 127–131 (2008) Abeßer, J., Dittmar, C., Großmann, H.: Automatic genre and artist classification by analyzing improvised solo parts from musical recordings. In: Proceedings of the Audio Mostly Conference, Piteå, Sweden, pp. 127–131 (2008)
2.
Zurück zum Zitat Abeßer, J., Lukashevich, H.M., Dittmar, C., Schuller, G.: Genre classification using bass-related high-level features and playing styles. In: Proceedings of the ISMIR, pp. 453–458 (2009) Abeßer, J., Lukashevich, H.M., Dittmar, C., Schuller, G.: Genre classification using bass-related high-level features and playing styles. In: Proceedings of the ISMIR, pp. 453–458 (2009)
3.
Zurück zum Zitat Abeßer, J., Lukashevich, H., Dittmar, C., Bräuer, P., Karuse, F.: Rule-based classification of musical genres from a global cultural background. In: Proceedings of the CMMR, pp. 317–336 (2010) Abeßer, J., Lukashevich, H., Dittmar, C., Bräuer, P., Karuse, F.: Rule-based classification of musical genres from a global cultural background. In: Proceedings of the CMMR, pp. 317–336 (2010)
4.
Zurück zum Zitat Abeßer, J., Bräuer, P., Lukashevich, H.M., Schuller, G.: Bass playing style detection based on high-level features and pattern similarity. In: Proceedings of the ISMIR, pp. 93–98 (2010) Abeßer, J., Bräuer, P., Lukashevich, H.M., Schuller, G.: Bass playing style detection based on high-level features and pattern similarity. In: Proceedings of the ISMIR, pp. 93–98 (2010)
5.
Zurück zum Zitat Abeßer, J., Lukashevich, H., Bräuer, P.: Classification of music genres based on repetitive basslines. J. New Music Res. 41(3), 239–257 (2012) Abeßer, J., Lukashevich, H., Bräuer, P.: Classification of music genres based on repetitive basslines. J. New Music Res. 41(3), 239–257 (2012)
6.
Zurück zum Zitat Ahonen, T.E.: Compressing lists for audio classification. In: Proceedings of the International Workshop on Machine Learning and Music. MML ’10, pp. 45–48. ACM, New York (2010) Ahonen, T.E.: Compressing lists for audio classification. In: Proceedings of the International Workshop on Machine Learning and Music. MML ’10, pp. 45–48. ACM, New York (2010)
7.
Zurück zum Zitat Ahrendt, P., Meng, A., Larsen, J.: Decision time horizon for music genre classification using short-time features. In: Proceedings of the EUSIPCO (2004) Ahrendt, P., Meng, A., Larsen, J.: Decision time horizon for music genre classification using short-time features. In: Proceedings of the EUSIPCO (2004)
8.
Zurück zum Zitat Ahrendt, P., Larsen, J., Goutte, C.: Co-occurrence models in music genre classification. In: Proceedings of the IEEE Workshop Machine Learning Signal Process, Sept 2005 Ahrendt, P., Larsen, J., Goutte, C.: Co-occurrence models in music genre classification. In: Proceedings of the IEEE Workshop Machine Learning Signal Process, Sept 2005
9.
Zurück zum Zitat Ahrendt, P.: Music genre classification systems - a computational approach. Ph.D. thesis, Technical University of Denmark (2006) Ahrendt, P.: Music genre classification systems - a computational approach. Ph.D. thesis, Technical University of Denmark (2006)
10.
Zurück zum Zitat Almoosa, N., Bae, S.H., Juang, B.H.: Feature extraction by incremental parsing for music indexing. In: Proceedings of the ICASSP, pp. 2410–2413, Mar 2010 Almoosa, N., Bae, S.H., Juang, B.H.: Feature extraction by incremental parsing for music indexing. In: Proceedings of the ICASSP, pp. 2410–2413, Mar 2010
11.
Zurück zum Zitat Anan, Y., Hatano, K., Bannai, H., Takeda, M.: Music genre classification using similarity functions. In: Proceedings of the ISMIR, pp. 693–698 (2011) Anan, Y., Hatano, K., Bannai, H., Takeda, M.: Music genre classification using similarity functions. In: Proceedings of the ISMIR, pp. 693–698 (2011)
12.
Zurück zum Zitat Andén, J., Mallat, S.: Multiscale scattering for audio classification. In: Proceedings of the ISMIR, pp. 657–662 (2011) Andén, J., Mallat, S.: Multiscale scattering for audio classification. In: Proceedings of the ISMIR, pp. 657–662 (2011)
13.
Zurück zum Zitat Anglade, A., Ramirez, R., Dixon, S.: Genre classification using harmony rules induced from automatic chord transcriptions. In: Proceedings of the ISMIR (2009) Anglade, A., Ramirez, R., Dixon, S.: Genre classification using harmony rules induced from automatic chord transcriptions. In: Proceedings of the ISMIR (2009)
14.
Zurück zum Zitat Anglade, A., Ramirez, R., Dixon, S.: First-order logic classification models of musical genres based on harmony. In: Proceedings of the SMC (2009) Anglade, A., Ramirez, R., Dixon, S.: First-order logic classification models of musical genres based on harmony. In: Proceedings of the SMC (2009)
15.
Zurück zum Zitat Anglade, A., Benetos, E., Mauch, M., Dixon, S.: Improving music genre classification using automatically induced harmony rules. J. New Music Res. 39(4), 349–361 (2010) Anglade, A., Benetos, E., Mauch, M., Dixon, S.: Improving music genre classification using automatically induced harmony rules. J. New Music Res. 39(4), 349–361 (2010)
16.
Zurück zum Zitat Annesi, P., Basili, R., Gitto, R., Moschitti, A., Petitti, R.: Audio feature engineering for automatic music genre classification. In: Proceedings of the Recherche d’Information Assistée par Ordinateur, Pittsburgh, Pennsylvania, pp. 702–711 (2007) Annesi, P., Basili, R., Gitto, R., Moschitti, A., Petitti, R.: Audio feature engineering for automatic music genre classification. In: Proceedings of the Recherche d’Information Assistée par Ordinateur, Pittsburgh, Pennsylvania, pp. 702–711 (2007)
17.
Zurück zum Zitat Arabi, A.F., Lu, G.: Enhanced polyphonic music genre classification using high level features. In: IEEE International Conference on Signal and Image Processing Applications (2009) Arabi, A.F., Lu, G.: Enhanced polyphonic music genre classification using high level features. In: IEEE International Conference on Signal and Image Processing Applications (2009)
18.
Zurück zum Zitat Arenas, J., Larsen, J., Hansen, L., Meng, A.: Optimal filtering of dynamics in short-time features for music organization. In: Proceedings of the ISMIR (2006) Arenas, J., Larsen, J., Hansen, L., Meng, A.: Optimal filtering of dynamics in short-time features for music organization. In: Proceedings of the ISMIR (2006)
19.
Zurück zum Zitat Ariyaratne, H., Zhang, D.: A novel automatic hierarchical approach to music genre classification. In: Proceedings of the ICME, pp. 564–569, July 2012 Ariyaratne, H., Zhang, D.: A novel automatic hierarchical approach to music genre classification. In: Proceedings of the ICME, pp. 564–569, July 2012
20.
Zurück zum Zitat Aryafar, K., Shokoufandeh, A.: Music genre classification using explicit semantic analysis. In: Proceedings of the ACM MIRUM Workshop, Scottsdale, AZ, USA, pp. 33–38, Nov 2011 Aryafar, K., Shokoufandeh, A.: Music genre classification using explicit semantic analysis. In: Proceedings of the ACM MIRUM Workshop, Scottsdale, AZ, USA, pp. 33–38, Nov 2011
21.
Zurück zum Zitat Aryafar, K., Jafarpour, S., Shokoufandeh, A.: Music genre classification using sparsity-eager support vector machines. Technical report, Drexel University (2012) Aryafar, K., Jafarpour, S., Shokoufandeh, A.: Music genre classification using sparsity-eager support vector machines. Technical report, Drexel University (2012)
22.
Zurück zum Zitat Aucouturier, J.J., Pachet, F.: Music similarity measures: what’s the use? In: Proceedings of the ISMIR, Paris, France, Oct 2002 Aucouturier, J.J., Pachet, F.: Music similarity measures: what’s the use? In: Proceedings of the ISMIR, Paris, France, Oct 2002
23.
Zurück zum Zitat Aucouturier, J.J., Pachet, F.: Representing music genre: a state of the art. J. New Music Res. 32(1), 83–93 (2003) Aucouturier, J.J., Pachet, F.: Representing music genre: a state of the art. J. New Music Res. 32(1), 83–93 (2003)
24.
Zurück zum Zitat Aucouturier, J.J., Pampalk, E.: Introduction - from genres to tags: a little epistemology of music information retrieval research. J. New Music Res. 37(2), 87–92 (2008) Aucouturier, J.J., Pampalk, E.: Introduction - from genres to tags: a little epistemology of music information retrieval research. J. New Music Res. 37(2), 87–92 (2008)
25.
Zurück zum Zitat Aucouturier, J.J.: Sounds like teen spirit: computational insights into the grounding of everyday musical terms. In: Minett, J., Wang, W. (eds.) Language, Evolution and the Brain. Frontiers in Linguistic Series. Academia Sinica Press, Taipei (2009) Aucouturier, J.J.: Sounds like teen spirit: computational insights into the grounding of everyday musical terms. In: Minett, J., Wang, W. (eds.) Language, Evolution and the Brain. Frontiers in Linguistic Series. Academia Sinica Press, Taipei (2009)
26.
Zurück zum Zitat Backer, E., van Kranenburg, P.: On musical stylometry - a pattern recognition approach. Pattern Recogn. Lett. 26, 299–309 (2005) Backer, E., van Kranenburg, P.: On musical stylometry - a pattern recognition approach. Pattern Recogn. Lett. 26, 299–309 (2005)
27.
Zurück zum Zitat Bağci, U., Erzin, E.: Automatic classification of musical genres using inter-genre similarity. IEEE Signal Proc. Lett. 14(8), 521–524 (2007) Bağci, U., Erzin, E.: Automatic classification of musical genres using inter-genre similarity. IEEE Signal Proc. Lett. 14(8), 521–524 (2007)
28.
Zurück zum Zitat Balkema, W.: Variable-size gaussian mixture models for music similarity measures. In: Proceedings of the ISMIR, pp. 491–494 (2007) Balkema, W.: Variable-size gaussian mixture models for music similarity measures. In: Proceedings of the ISMIR, pp. 491–494 (2007)
29.
Zurück zum Zitat Balkema, W., van der Heijden, F.: Music playlist generation by assimilating GMMs into SOMs. Pattern Recogn. Lett. 31(1), 1396–1402 (2010) Balkema, W., van der Heijden, F.: Music playlist generation by assimilating GMMs into SOMs. Pattern Recogn. Lett. 31(1), 1396–1402 (2010)
30.
Zurück zum Zitat Barbedo, J.G.A., Lopes, A.: Automatic genre classification of musical signals. EURASIP J. Adv. Signal Process. 2007, 1–12 (2007)MathSciNet Barbedo, J.G.A., Lopes, A.: Automatic genre classification of musical signals. EURASIP J. Adv. Signal Process. 2007, 1–12 (2007)MathSciNet
31.
Zurück zum Zitat Barbedo, J.G.A., Lopes, A.: Automatic musical genre classification using a flexible approach. J. Audio Eng. Soc. 56(7/8), 560–568 (2008) Barbedo, J.G.A., Lopes, A.: Automatic musical genre classification using a flexible approach. J. Audio Eng. Soc. 56(7/8), 560–568 (2008)
32.
Zurück zum Zitat Barbieri, G., Esposti, M.D., Pachet, F., Roy, P.: Is there a relation between the syntax and the fitness of an audio feature? In: Proceedings of the ISMIR (2010) Barbieri, G., Esposti, M.D., Pachet, F., Roy, P.: Is there a relation between the syntax and the fitness of an audio feature? In: Proceedings of the ISMIR (2010)
33.
Zurück zum Zitat Barreira, L., Cavaco, S., da Silva, J.: Unsupervised music genre classification with a model-based approach. In: Proceedings of the Portuguese Conference on Progress in Artificial Intelligence, pp. 268–281 (2011) Barreira, L., Cavaco, S., da Silva, J.: Unsupervised music genre classification with a model-based approach. In: Proceedings of the Portuguese Conference on Progress in Artificial Intelligence, pp. 268–281 (2011)
34.
Zurück zum Zitat Basili, R., Serafini, A., Stellato, A.: Classification of musical genre: a machine learning approach. In: Proceedings of the ISMIR (2004) Basili, R., Serafini, A., Stellato, A.: Classification of musical genre: a machine learning approach. In: Proceedings of the ISMIR (2004)
35.
Zurück zum Zitat Behun, K.: Image features in music style recognition. In: Proceedings of the Central European Seminar on Computer Graphics (2012) Behun, K.: Image features in music style recognition. In: Proceedings of the Central European Seminar on Computer Graphics (2012)
36.
Zurück zum Zitat Benetos, E., Kotropoulos, C.: A tensor-based approach for automatic music genre classification. In: Proceedings of the EUSIPCO, Lausanne, Switzerland (2008) Benetos, E., Kotropoulos, C.: A tensor-based approach for automatic music genre classification. In: Proceedings of the EUSIPCO, Lausanne, Switzerland (2008)
37.
Zurück zum Zitat Benetos, E., Kotropoulos, C.: Non-negative tensor factorization applied to music genre classification. IEEE Trans. Audio Speech Lang. Process. 18(8), 1955–1967 (2010) Benetos, E., Kotropoulos, C.: Non-negative tensor factorization applied to music genre classification. IEEE Trans. Audio Speech Lang. Process. 18(8), 1955–1967 (2010)
38.
Zurück zum Zitat Bergstra, J., Casagrande, N., Erhan, D., Eck, D., Kégl, B.: Aggregate features and Adaboost for music classification. Mach. Learn. 65(2–3), 473–484 (2006) Bergstra, J., Casagrande, N., Erhan, D., Eck, D., Kégl, B.: Aggregate features and Adaboost for music classification. Mach. Learn. 65(2–3), 473–484 (2006)
39.
Zurück zum Zitat Bergstra, J.: Algorithms for classifying recorded music by genre. Master’s thesis, Université de Montréal, Montréal, Canada, Aug 2006 Bergstra, J.: Algorithms for classifying recorded music by genre. Master’s thesis, Université de Montréal, Montréal, Canada, Aug 2006
40.
Zurück zum Zitat Bergstra, J., Lacoste, A., Eck, D.: Predicting genre labels for artist using FreeDB. In: Proceedings of the ISMIR, pp. 85–88 (2006) Bergstra, J., Lacoste, A., Eck, D.: Predicting genre labels for artist using FreeDB. In: Proceedings of the ISMIR, pp. 85–88 (2006)
41.
Zurück zum Zitat Bergstra, J., Mandel, M., Eck, D.: Scalable genre and tag prediction with spectral covariance. In: Proceedings of the ISMIR (2010) Bergstra, J., Mandel, M., Eck, D.: Scalable genre and tag prediction with spectral covariance. In: Proceedings of the ISMIR (2010)
42.
Zurück zum Zitat Bertin-Mahieux, T., Weiss, R.J., Ellis, D.P.W.: Clustering beat-chroma patterns in a large music database. In: Proceedings of the ISMIR, Utrecht, Netherlands, Aug 2010 Bertin-Mahieux, T., Weiss, R.J., Ellis, D.P.W.: Clustering beat-chroma patterns in a large music database. In: Proceedings of the ISMIR, Utrecht, Netherlands, Aug 2010
43.
Zurück zum Zitat Bickerstaffe, A.C., Makalic, E.: MML classification of music genres. In: Gedeon, T.T.D., Fung, L.C.C. (eds.) AI 2003. LNCS (LNAI), vol. 2903, pp. 1063–1071. Springer, Heidelberg (2003) Bickerstaffe, A.C., Makalic, E.: MML classification of music genres. In: Gedeon, T.T.D., Fung, L.C.C. (eds.) AI 2003. LNCS (LNAI), vol. 2903, pp. 1063–1071. Springer, Heidelberg (2003)
44.
Zurück zum Zitat Bigerelle, M., Iost, A.: Fractal dimension and classification of music. Chaos Soliton. Fract. 11(14), 2179–2192 (2000) Bigerelle, M., Iost, A.: Fractal dimension and classification of music. Chaos Soliton. Fract. 11(14), 2179–2192 (2000)
45.
Zurück zum Zitat Blume, H., Haller, M., Botteck, M., Theimer, W.: Perceptual feature based music classification - a DSP perspective for a new type of application. In: International Conference on Embedded Computer Systems (2008) Blume, H., Haller, M., Botteck, M., Theimer, W.: Perceptual feature based music classification - a DSP perspective for a new type of application. In: International Conference on Embedded Computer Systems (2008)
46.
Zurück zum Zitat Bogdanov, D., Serra, J., Wack, N., Herrera, P., Serra, X.: Unifying low-level and high-level music similarity measures. IEEE Trans. Multimed. 13(4), 687–701 (2011) Bogdanov, D., Serra, J., Wack, N., Herrera, P., Serra, X.: Unifying low-level and high-level music similarity measures. IEEE Trans. Multimed. 13(4), 687–701 (2011)
47.
Zurück zum Zitat Brecheisen, S., Kriegel, H.P., Kunath, P., Pryakhin, A.: Hierarchical genre classification for large music collections. In: Proceedings of the ICME, pp. 1385–1388, July 2006 Brecheisen, S., Kriegel, H.P., Kunath, P., Pryakhin, A.: Hierarchical genre classification for large music collections. In: Proceedings of the ICME, pp. 1385–1388, July 2006
48.
Zurück zum Zitat Burred, J., Lerch, A.: A hierarchical approach to automatic musical genre classification. In: Proceedings of the DAFx, London, UK, Sept 2003 Burred, J., Lerch, A.: A hierarchical approach to automatic musical genre classification. In: Proceedings of the DAFx, London, UK, Sept 2003
49.
Zurück zum Zitat Burred, J.J., Lerch, A.: Hierarchical automatic audio signal classification. J. Audio Eng. Soc. 52(7), 724–739 (2004) Burred, J.J., Lerch, A.: Hierarchical automatic audio signal classification. J. Audio Eng. Soc. 52(7), 724–739 (2004)
50.
Zurück zum Zitat Burred, J.J., Peeters, G.: An adaptive system for music classification and tagging. In: International Workshop on Learning Semantics of Audio Signals (2009) Burred, J.J., Peeters, G.: An adaptive system for music classification and tagging. In: International Workshop on Learning Semantics of Audio Signals (2009)
51.
Zurück zum Zitat Casey, M., Veltkamp, R., Goto, M., Leman, M., Rhodes, C., Slaney, M.: Content-based music information retrieval: current directions and future challenges. Proc. IEEE 96(4), 668–696 (2008) Casey, M., Veltkamp, R., Goto, M., Leman, M., Rhodes, C., Slaney, M.: Content-based music information retrieval: current directions and future challenges. Proc. IEEE 96(4), 668–696 (2008)
52.
Zurück zum Zitat Cataltepe, Z., Yaslan, Y., Sonmez, A.: Music genre classification using MIDI and audio features. EURASIP J. Adv. Signal Process. 2007, 1–8 (2007) Cataltepe, Z., Yaslan, Y., Sonmez, A.: Music genre classification using MIDI and audio features. EURASIP J. Adv. Signal Process. 2007, 1–8 (2007)
53.
Zurück zum Zitat Chai, W., Vercoe, B.: Folk music classification using hidden Markov models. In: International Conference on Artificial Intelligence (2001) Chai, W., Vercoe, B.: Folk music classification using hidden Markov models. In: International Conference on Artificial Intelligence (2001)
54.
Zurück zum Zitat Chang, L., Yu, X., Wan, W., Yao, J.: Research on fast music classification based on SVM in compressed domain. In: Proceedings of the ICALIP, pp. 638–642, July 2008 Chang, L., Yu, X., Wan, W., Yao, J.: Research on fast music classification based on SVM in compressed domain. In: Proceedings of the ICALIP, pp. 638–642, July 2008
55.
Zurück zum Zitat Chang, K., Jang, J.S.R., Iliopoulos, C.S.: Music genre classification via compressive sampling. In: Proceedings of the ISMIR, Amsterdam, The Netherlands, pp. 387–392, Aug 2010 Chang, K., Jang, J.S.R., Iliopoulos, C.S.: Music genre classification via compressive sampling. In: Proceedings of the ISMIR, Amsterdam, The Netherlands, pp. 387–392, Aug 2010
56.
Zurück zum Zitat Charami, M., Halloush, R., Tsekeridou, S.: Performance evaluation of TreeQ and LVQ classifiers for music information retrieval. In: Boukis, C., Pnevmatikakis, L., Polymenakos, L., et al. (eds.) Artificial Intelligence and Innovations 2007: From Theory to Applications. IFIP, vol. 247, pp. 331–338. Springer, Boston (2007) Charami, M., Halloush, R., Tsekeridou, S.: Performance evaluation of TreeQ and LVQ classifiers for music information retrieval. In: Boukis, C., Pnevmatikakis, L., Polymenakos, L., et al. (eds.) Artificial Intelligence and Innovations 2007: From Theory to Applications. IFIP, vol. 247, pp. 331–338. Springer, Boston (2007)
57.
Zurück zum Zitat Charbuillet, C., Tardieu, D., Peeters, G.: GMM supervector for content based music similarity. In: Proceedings of the DAFx, Paris, France, Sept 2011 Charbuillet, C., Tardieu, D., Peeters, G.: GMM supervector for content based music similarity. In: Proceedings of the DAFx, Paris, France, Sept 2011
58.
Zurück zum Zitat Chase, A.: Music discriminations by carp “Cyprinus carpio”. Learn. Behav. 29, 336–353 (2001) Chase, A.: Music discriminations by carp “Cyprinus carpio”. Learn. Behav. 29, 336–353 (2001)
59.
Zurück zum Zitat Chathuranga, D., Jayaratne, L.: Musical genre classification using ensemble of classifiers. In: Proceedings of the International Conference on Computational Intelligence, Modelling and Simulation, pp. 237–242, Sept 2012 Chathuranga, D., Jayaratne, L.: Musical genre classification using ensemble of classifiers. In: Proceedings of the International Conference on Computational Intelligence, Modelling and Simulation, pp. 237–242, Sept 2012
60.
Zurück zum Zitat Chen, K., Gao, S., Zhu, Y., Sun, Q.: Music genres classification using text categorization method. In: Proceedings of the IEEE Workshop on Multimedia Signal Processing, pp. 221–224, Oct 2006 Chen, K., Gao, S., Zhu, Y., Sun, Q.: Music genres classification using text categorization method. In: Proceedings of the IEEE Workshop on Multimedia Signal Processing, pp. 221–224, Oct 2006
61.
Zurück zum Zitat Chen, G., Wang, T., Herrera, P.: Relevance feedback in an adaptive space with one-class SVM for content-based music retrieval. In: Proceedings of the ICALIP, pp. 1153–1158, July 2008 Chen, G., Wang, T., Herrera, P.: Relevance feedback in an adaptive space with one-class SVM for content-based music retrieval. In: Proceedings of the ICALIP, pp. 1153–1158, July 2008
62.
Zurück zum Zitat Chen, L., Wright, P., Nejdl, W.: Improving music genre classification using collaborative tagging data. In: International Conference on Web Search and Data Mining, Barcelona, Spain, Feb 2009 Chen, L., Wright, P., Nejdl, W.: Improving music genre classification using collaborative tagging data. In: International Conference on Web Search and Data Mining, Barcelona, Spain, Feb 2009
63.
Zurück zum Zitat Chen, S.H., Chen, S.H.: Content-based music genre classification using timbral feature vectors and support vector machine. In: Proceedings of the International Conference on Interaction Sciences, pp. 1095–1101, Nov 2009 Chen, S.H., Chen, S.H.: Content-based music genre classification using timbral feature vectors and support vector machine. In: Proceedings of the International Conference on Interaction Sciences, pp. 1095–1101, Nov 2009
64.
Zurück zum Zitat Chen, S.H., Chen, S.H., Guido, R.C.: Music genre classification algorithm based on dynamic frame analysis and support vector machine. In: IEEE International Symposium on Multimedia (2010) Chen, S.H., Chen, S.H., Guido, R.C.: Music genre classification algorithm based on dynamic frame analysis and support vector machine. In: IEEE International Symposium on Multimedia (2010)
65.
Zurück zum Zitat Chew, E., Volk, A., Lee, C.Y.: Dance music classification using inner metric analysis. In: Golden, B., Raghavan, S., Wasil, E. (eds.) The Next Wave in Computing, Optimization, and Decision Technologies. Proceedings of the INFORMS Computing Society Conference, pp. 355–370. Kluwer, Dordrecht (2005) Chew, E., Volk, A., Lee, C.Y.: Dance music classification using inner metric analysis. In: Golden, B., Raghavan, S., Wasil, E. (eds.) The Next Wave in Computing, Optimization, and Decision Technologies. Proceedings of the INFORMS Computing Society Conference, pp. 355–370. Kluwer, Dordrecht (2005)
66.
Zurück zum Zitat Cilibrasi, R., Vitányi, P., de Wolf, R.: Algorithmic clustering of music based on string compression. Comput. Music J. 28(4), 49–67 (2004) Cilibrasi, R., Vitányi, P., de Wolf, R.: Algorithmic clustering of music based on string compression. Comput. Music J. 28(4), 49–67 (2004)
67.
Zurück zum Zitat Cilibrasi, R., Vitanyi, P.: Clustering by compression. IEEE Trans. Inf. Theory 51(4), 1523–1545 (2005)MathSciNetMATH Cilibrasi, R., Vitanyi, P.: Clustering by compression. IEEE Trans. Inf. Theory 51(4), 1523–1545 (2005)MathSciNetMATH
68.
Zurück zum Zitat Collins, N.: Influence in early electronic dance music: an audio content analysis investigation. In: Proceedings of the ISMIR (2012) Collins, N.: Influence in early electronic dance music: an audio content analysis investigation. In: Proceedings of the ISMIR (2012)
69.
Zurück zum Zitat Conklin, D.: Melodic analysis with segment classes. Mach. Learn. 65, 349–360 (2006) Conklin, D.: Melodic analysis with segment classes. Mach. Learn. 65, 349–360 (2006)
70.
Zurück zum Zitat Conklin, D.: Melody classification using patterns. In: Proceedings of the International Workshop on Machine Learning and Music, pp. 37–41 (2009) Conklin, D.: Melody classification using patterns. In: Proceedings of the International Workshop on Machine Learning and Music, pp. 37–41 (2009)
71.
Zurück zum Zitat Cornelis, O., Lesaffre, M., Moelants, D., Leman, M.: Access to ethnic music: advances and perspectives in content-based music information retrieval. Signal Process. 90(4), 1008–1031 (2010)MATH Cornelis, O., Lesaffre, M., Moelants, D., Leman, M.: Access to ethnic music: advances and perspectives in content-based music information retrieval. Signal Process. 90(4), 1008–1031 (2010)MATH
72.
Zurück zum Zitat Correa, D.C., Saito, J.H., da Costa, L.F.: Musical genres: beating to the rhythms of different drums. New. J. Phys. 12(5), 053030 (2010) Correa, D.C., Saito, J.H., da Costa, L.F.: Musical genres: beating to the rhythms of different drums. New. J. Phys. 12(5), 053030 (2010)
73.
Zurück zum Zitat Costa, C.H.L., Valle Jr., J.D., Koerich, A.L.: Automatic classification of audio data. In: Proceedings of the IEEE International Conference on Systems, Man and Cybernetics, pp. 562–567 (2004) Costa, C.H.L., Valle Jr., J.D., Koerich, A.L.: Automatic classification of audio data. In: Proceedings of the IEEE International Conference on Systems, Man and Cybernetics, pp. 562–567 (2004)
74.
Zurück zum Zitat Costa, Y.M.G., Oliveira, L.S., Koerich, A.L., Gouyon, F.: Music genre recognition using spectrograms. In: Proceedings of the International Conference on Systems, Signals and Image Processing (2011) Costa, Y.M.G., Oliveira, L.S., Koerich, A.L., Gouyon, F.: Music genre recognition using spectrograms. In: Proceedings of the International Conference on Systems, Signals and Image Processing (2011)
75.
Zurück zum Zitat Costa, Y., Oliveira, L., Koerich, A., Gouyon, F., Martins, J.: Music genre classification using LBP textural features. Signal Process. 92(11), 2723–2737 (2012) Costa, Y., Oliveira, L., Koerich, A., Gouyon, F., Martins, J.: Music genre classification using LBP textural features. Signal Process. 92(11), 2723–2737 (2012)
76.
Zurück zum Zitat Costa, Y.M.G., Oliveira, L.S., Koerich, A.L., Gouyon, F.: Comparing textural features for music genre classification. In: Proceedings of the IEEE World Congress on Computational Intelligence, June 2012 Costa, Y.M.G., Oliveira, L.S., Koerich, A.L., Gouyon, F.: Comparing textural features for music genre classification. In: Proceedings of the IEEE World Congress on Computational Intelligence, June 2012
77.
Zurück zum Zitat Craft, A., Wiggins, G.A., Crawform, T.: How many beans make five? The consensus problem in music-genre classification and a new evaluation method for single-genre categorisation systems. In: Proceedings of the ISMIR (2007) Craft, A., Wiggins, G.A., Crawform, T.: How many beans make five? The consensus problem in music-genre classification and a new evaluation method for single-genre categorisation systems. In: Proceedings of the ISMIR (2007)
78.
Zurück zum Zitat Craft, A.: The role of culture in the music genre classification task: human behaviour and its effect on methodology and evaluation. Technical report, Queen Mary University of London, Nov 2007 Craft, A.: The role of culture in the music genre classification task: human behaviour and its effect on methodology and evaluation. Technical report, Queen Mary University of London, Nov 2007
79.
Zurück zum Zitat Crump, M.: A principal components approach to the perception of musical style. Master’s thesis, University of Lethbridge (2002) Crump, M.: A principal components approach to the perception of musical style. Master’s thesis, University of Lethbridge (2002)
80.
Zurück zum Zitat Cruz-Alcáza, P.P., Vidal-Ruiz, E.: Modeling musical style using grammatical inference techniques: a tool for classifying and generating melodies. In: Proceedings of the WEDELMUSIC, pp. 77–84, Sept 2003 Cruz-Alcáza, P.P., Vidal-Ruiz, E.: Modeling musical style using grammatical inference techniques: a tool for classifying and generating melodies. In: Proceedings of the WEDELMUSIC, pp. 77–84, Sept 2003
81.
Zurück zum Zitat Cruz-Alcázar, P.P., Vidal-Ruiz, E., Pérez-Cortés, J.C.: Musical style identification using grammatical inference: the encoding problem. In: Sanfeliu, A., Ruiz-Shulcloper, J. (eds.) CIARP 2003. LNCS, vol. 2905, pp. 375–382. Springer, Heidelberg (2003) Cruz-Alcázar, P.P., Vidal-Ruiz, E., Pérez-Cortés, J.C.: Musical style identification using grammatical inference: the encoding problem. In: Sanfeliu, A., Ruiz-Shulcloper, J. (eds.) CIARP 2003. LNCS, vol. 2905, pp. 375–382. Springer, Heidelberg (2003)
82.
Zurück zum Zitat Cruz-Alcáza, P.P., Vidal-Ruiz, E.: Two grammatical inference applications in music processing. Appl. Artif. Intell. 22(1/2), 53–76 (2008) Cruz-Alcáza, P.P., Vidal-Ruiz, E.: Two grammatical inference applications in music processing. Appl. Artif. Intell. 22(1/2), 53–76 (2008)
83.
Zurück zum Zitat Dannenberg, R.B., Thom, B., Watson, D.: A machine learning approach to musical style recognition. In: Proceedings of the ICMC, pp. 344–347 (1997) Dannenberg, R.B., Thom, B., Watson, D.: A machine learning approach to musical style recognition. In: Proceedings of the ICMC, pp. 344–347 (1997)
84.
Zurück zum Zitat Dannenberg, R., Foote, J., Tzanetakis, G., Weare, C.: Panel: new directions in music information retrieval. In: Proceedings of the ICMC (2001) Dannenberg, R., Foote, J., Tzanetakis, G., Weare, C.: Panel: new directions in music information retrieval. In: Proceedings of the ICMC (2001)
85.
Zurück zum Zitat Dannenberg, R.B.: Style in music. In: Argamon, S., Burns, K., Dubnov, S. (eds.) The Structure of Style, pp. 45–57. Springer, Heidelberg (2010) Dannenberg, R.B.: Style in music. In: Argamon, S., Burns, K., Dubnov, S. (eds.) The Structure of Style, pp. 45–57. Springer, Heidelberg (2010)
86.
Zurück zum Zitat DeCoro, C., Barutcuoglu, S., Fiebrink, R.: Bayesian aggregation for hierarchical genre classification. In: Proceedings of the ISMIR (2007) DeCoro, C., Barutcuoglu, S., Fiebrink, R.: Bayesian aggregation for hierarchical genre classification. In: Proceedings of the ISMIR (2007)
87.
Zurück zum Zitat Dehghani, M., Lovett, A.M.: Efficient genre classification using qualitative representations. In: Proceedings of the ISMIR, pp. 353–354 (2006) Dehghani, M., Lovett, A.M.: Efficient genre classification using qualitative representations. In: Proceedings of the ISMIR, pp. 353–354 (2006)
88.
Zurück zum Zitat Dellandrea, E., Harb, H., Chen, L.: Zipf, neural networks and SVM for musical genre classification. In: Proceedings of the IEEE International Symposium on Signal Processing and Information Technology, pp. 57–62, Dec 2005 Dellandrea, E., Harb, H., Chen, L.: Zipf, neural networks and SVM for musical genre classification. In: Proceedings of the IEEE International Symposium on Signal Processing and Information Technology, pp. 57–62, Dec 2005
89.
Zurück zum Zitat Deshpande, H., Singh, R., Nam, U.: Classification of music signals in the visual domain. In: Proceedings of the DAFx, Limerick, Ireland, Dec 2001 Deshpande, H., Singh, R., Nam, U.: Classification of music signals in the visual domain. In: Proceedings of the DAFx, Limerick, Ireland, Dec 2001
90.
Zurück zum Zitat Dieleman, S., Brakel, P., Schrauwen, B.: Audio-based music classification with a pretrained convolutional network. In: Proceedings of the ISMIR (2011) Dieleman, S., Brakel, P., Schrauwen, B.: Audio-based music classification with a pretrained convolutional network. In: Proceedings of the ISMIR (2011)
91.
Zurück zum Zitat Diodati, P., Piazza, S.: Different amplitude and time distribution of the sound of light and classical music. Eur. Phys. J. B - Condens. Matter Complex Syst. 17, 143–145 (2000) Diodati, P., Piazza, S.: Different amplitude and time distribution of the sound of light and classical music. Eur. Phys. J. B - Condens. Matter Complex Syst. 17, 143–145 (2000)
92.
Zurück zum Zitat Dixon, S., Pampalk, E., Widmer, G.: Classification of dance music by periodicity patterns. In: Proceedings of the ISMIR (2003) Dixon, S., Pampalk, E., Widmer, G.: Classification of dance music by periodicity patterns. In: Proceedings of the ISMIR (2003)
93.
Zurück zum Zitat Dixon, S., Gouyon, F., Widmer, G.: Towards characterisation of music via rhythmic patterns. In: Proceedings of the ISMIR, Barcelona, Spain, pp. 509–517 (2004) Dixon, S., Gouyon, F., Widmer, G.: Towards characterisation of music via rhythmic patterns. In: Proceedings of the ISMIR, Barcelona, Spain, pp. 509–517 (2004)
94.
Zurück zum Zitat Dixon, S., Mauch, M., Anglade, A.: Probabilistic and logic-based modelling of harmony. In: Ystad, S., Aramaki, M., Kronland-Martinet, R., Jensen, K. (eds.) CMMR 2010. LNCS, vol. 6684, pp. 1–19. Springer, Heidelberg (2011) Dixon, S., Mauch, M., Anglade, A.: Probabilistic and logic-based modelling of harmony. In: Ystad, S., Aramaki, M., Kronland-Martinet, R., Jensen, K. (eds.) CMMR 2010. LNCS, vol. 6684, pp. 1–19. Springer, Heidelberg (2011)
95.
Zurück zum Zitat Dor, O., Reich, Y.: An evaluation of musical score characteristics for automatic classification of composers. Comput. Music J. 35(3), 86–97 (2011) Dor, O., Reich, Y.: An evaluation of musical score characteristics for automatic classification of composers. Comput. Music J. 35(3), 86–97 (2011)
96.
Zurück zum Zitat Doraisamy, S., Golzari, S., Norowi, N.M., Sulaiman, M.N.B., Udzir, N.I.: A study on feature selection and classification techniques for automatic genre classification of traditional Malay music. In: Proceedings of the ISMIR, Philadelphia, PA (2008) Doraisamy, S., Golzari, S., Norowi, N.M., Sulaiman, M.N.B., Udzir, N.I.: A study on feature selection and classification techniques for automatic genre classification of traditional Malay music. In: Proceedings of the ISMIR, Philadelphia, PA (2008)
97.
Zurück zum Zitat Doraisamy, S., Golzari, S.: Automatic musical genre classification and artificial immune recognition system. In: Raś, Z.W., Wieczorkowska, A.A. (eds.) Advances in Music Information Retrieval. SCI, vol. 274, pp. 390–402. Springer, Heidelberg (2010) Doraisamy, S., Golzari, S.: Automatic musical genre classification and artificial immune recognition system. In: Raś, Z.W., Wieczorkowska, A.A. (eds.) Advances in Music Information Retrieval. SCI, vol. 274, pp. 390–402. Springer, Heidelberg (2010)
98.
Zurück zum Zitat Doudpota, S.M., Guha, S.: Mining movies for song sequences with video based music genre identification system. Int. J. Info. Process. Manag. 49(2), 529–544 (2013) Doudpota, S.M., Guha, S.: Mining movies for song sequences with video based music genre identification system. Int. J. Info. Process. Manag. 49(2), 529–544 (2013)
99.
Zurück zum Zitat Downie, J., Ehmann, A., Tcheng, D.: Real-time genre classification for music digital libraries. In: Proceedings of the Joint ACM/IEEE Conference on Digital Libraries, p. 377, June 2005 Downie, J., Ehmann, A., Tcheng, D.: Real-time genre classification for music digital libraries. In: Proceedings of the Joint ACM/IEEE Conference on Digital Libraries, p. 377, June 2005
100.
Zurück zum Zitat Downie, J.S.: The music information retrieval evaluation exchange (2005–2007): a window into music information retrieval research. Acoust. Sci. Technol. 29(4), 247–255 (2008) Downie, J.S.: The music information retrieval evaluation exchange (2005–2007): a window into music information retrieval research. Acoust. Sci. Technol. 29(4), 247–255 (2008)
101.
Zurück zum Zitat Downie, J.S., Ehmann, A.F., Bay, M., Jones, M.C.: The music information retrieval evaluation exchange: some observations and insights. In: Raś, Z.W., Wieczorkowska, A.A. (eds.) Advances in Music Information Retrieval. SCI, vol. 274, pp. 93–115. Springer, Heidelberg (2010) Downie, J.S., Ehmann, A.F., Bay, M., Jones, M.C.: The music information retrieval evaluation exchange: some observations and insights. In: Raś, Z.W., Wieczorkowska, A.A. (eds.) Advances in Music Information Retrieval. SCI, vol. 274, pp. 93–115. Springer, Heidelberg (2010)
102.
Zurück zum Zitat Draman, N.A., Wilson, C., Ling, S.: Modified AIS-based classifier for music genre classification. In: Proceedings of the ISMIR, pp. 369–374 (2010) Draman, N.A., Wilson, C., Ling, S.: Modified AIS-based classifier for music genre classification. In: Proceedings of the ISMIR, pp. 369–374 (2010)
103.
Zurück zum Zitat Draman, N.A., Ahmad, S., Muda, A.K.: Recognizing patterns of music signals to songs classification using modified AIS-based classifier. In: Zain, J.M., Wan Mohd, W.M., El-Qawasmeh, E. (eds.) ICSECS 2011, Part II. CCIS, vol. 180, pp. 724–737. Springer, Heidelberg (2011) Draman, N.A., Ahmad, S., Muda, A.K.: Recognizing patterns of music signals to songs classification using modified AIS-based classifier. In: Zain, J.M., Wan Mohd, W.M., El-Qawasmeh, E. (eds.) ICSECS 2011, Part II. CCIS, vol. 180, pp. 724–737. Springer, Heidelberg (2011)
104.
Zurück zum Zitat Dunker, P., Dittmar, C., Begau, A., Nowak, S., Gruhne, M.: Semantic high-level features for automated cross-modal slideshow generation. In: Proceedings of the Content-Based Multimedia Indexing, pp. 144–149 (2009) Dunker, P., Dittmar, C., Begau, A., Nowak, S., Gruhne, M.: Semantic high-level features for automated cross-modal slideshow generation. In: Proceedings of the Content-Based Multimedia Indexing, pp. 144–149 (2009)
105.
Zurück zum Zitat Esmaili, S., Krishnan, S., Raahemifar, K.: Content based audio classification and retrieval using joint time-frequency analysis. In: Proceedings of the ICASSP, vol. 5, pp. 665–668 (2004) Esmaili, S., Krishnan, S., Raahemifar, K.: Content based audio classification and retrieval using joint time-frequency analysis. In: Proceedings of the ICASSP, vol. 5, pp. 665–668 (2004)
106.
Zurück zum Zitat Ezzaidi, H., Rouat, J.: Comparison of the statistical and information theory measures: Application to automatic musical genre classification. In: Proceedings of the IEEE Workshop on Machine Learning for Signal Processing, pp. 241–246, Aug 2007 Ezzaidi, H., Rouat, J.: Comparison of the statistical and information theory measures: Application to automatic musical genre classification. In: Proceedings of the IEEE Workshop on Machine Learning for Signal Processing, pp. 241–246, Aug 2007
107.
Zurück zum Zitat Ezzaidi, H., Bahoura, M., Rouat, J.: Taxonomy of musical genres. In: International Conference on Signal Image Technology and Internet Based Systems (2009) Ezzaidi, H., Bahoura, M., Rouat, J.: Taxonomy of musical genres. In: International Conference on Signal Image Technology and Internet Based Systems (2009)
108.
Zurück zum Zitat Fadeev, A., Missaoui, O., Frigui, H.: Dominant audio descriptors for audio classification and retrieval. In: Proceedings of the ICMLA, Louisville, KY, USA, pp. 75–78, Dec 2009 Fadeev, A., Missaoui, O., Frigui, H.: Dominant audio descriptors for audio classification and retrieval. In: Proceedings of the ICMLA, Louisville, KY, USA, pp. 75–78, Dec 2009
109.
Zurück zum Zitat Feng, Y., Dou, H., Qian, Y.: A study of audio classification on using different feature schemes with three classifiers. In: Proceedings of the International Conference on Information, Networking, Automation, pp. 298–302 (2010) Feng, Y., Dou, H., Qian, Y.: A study of audio classification on using different feature schemes with three classifiers. In: Proceedings of the International Conference on Information, Networking, Automation, pp. 298–302 (2010)
110.
Zurück zum Zitat Fernández, F., Chávez, F., Alcala, R., Herrera, F.: Musical genre classification by means of fuzzy rule-based systems: a preliminary approach. In: IEEE Congress on Evolutionary Computation (2011) Fernández, F., Chávez, F., Alcala, R., Herrera, F.: Musical genre classification by means of fuzzy rule-based systems: a preliminary approach. In: IEEE Congress on Evolutionary Computation (2011)
111.
Zurück zum Zitat Fernández, F., Chávez, F.: Fuzzy rule based system ensemble for music genre classification. In: Machado, P., Romero, J., Carballal, A. (eds.) EvoMUSART 2012. LNCS, vol. 7247, pp. 84–95. Springer, Heidelberg (2012) Fernández, F., Chávez, F.: Fuzzy rule based system ensemble for music genre classification. In: Machado, P., Romero, J., Carballal, A. (eds.) EvoMUSART 2012. LNCS, vol. 7247, pp. 84–95. Springer, Heidelberg (2012)
112.
Zurück zum Zitat Fiebrink, R., Fujinaga, I.: Feature selection pitfalls and music classification. In: Proceedings of the ISMIR, Victoria, BC, Canada, pp. 340–341 (2006) Fiebrink, R., Fujinaga, I.: Feature selection pitfalls and music classification. In: Proceedings of the ISMIR, Victoria, BC, Canada, pp. 340–341 (2006)
113.
Zurück zum Zitat Fiebrink, R.: An exploration of feature selection as a tool for optimizing musical genre classification. Master’s thesis, McGill University, June 2006 Fiebrink, R.: An exploration of feature selection as a tool for optimizing musical genre classification. Master’s thesis, McGill University, June 2006
114.
Zurück zum Zitat Flexer, A., Pampalk, E., Widmer, G.: Hidden Markov models for spectral similarity of songs. In: Proceedings of the DAFx, Madrid, Spain, Sept 2005 Flexer, A., Pampalk, E., Widmer, G.: Hidden Markov models for spectral similarity of songs. In: Proceedings of the DAFx, Madrid, Spain, Sept 2005
115.
Zurück zum Zitat Flexer, A., Gouyon, F., Dixon, S., Widmer, G.: Probabilistic combination of features for music classification. In: Proceedings of the ISMIR, Victoria, BC, Canada, pp. 111–114, Oct 2006 Flexer, A., Gouyon, F., Dixon, S., Widmer, G.: Probabilistic combination of features for music classification. In: Proceedings of the ISMIR, Victoria, BC, Canada, pp. 111–114, Oct 2006
116.
Zurück zum Zitat Flexer, A.: Statistical evaluation of music information retrieval experiments. J. New Music Res. 35(2), 113–120 (2006) Flexer, A.: Statistical evaluation of music information retrieval experiments. J. New Music Res. 35(2), 113–120 (2006)
117.
Zurück zum Zitat Flexer, A.: A closer look on artist filters for musical genre classification. In: Proceedings of the ISMIR, Vienna, Austria, Sept 2007 Flexer, A.: A closer look on artist filters for musical genre classification. In: Proceedings of the ISMIR, Vienna, Austria, Sept 2007
118.
Zurück zum Zitat Flexer, A., Schnitzer, D.: Album and artist effects for audio similarity at the scale of the web. In: Proceedings of the SMC, Porto, Portugal, pp. 59–64, July 2009 Flexer, A., Schnitzer, D.: Album and artist effects for audio similarity at the scale of the web. In: Proceedings of the SMC, Porto, Portugal, pp. 59–64, July 2009
119.
Zurück zum Zitat Flexer, A., Schnitzer, D.: Effects of album and artist filters in audio similarity computed for very large music databases. Comput. Music J. 34(3), 20–28 (2010) Flexer, A., Schnitzer, D.: Effects of album and artist filters in audio similarity computed for very large music databases. Comput. Music J. 34(3), 20–28 (2010)
120.
Zurück zum Zitat Frederico, G.: Classification into musical genres using a rhythmic kernel. In: Proceedings of the SMC (2004) Frederico, G.: Classification into musical genres using a rhythmic kernel. In: Proceedings of the SMC (2004)
121.
Zurück zum Zitat Fu, Z., Lu, G., Ting, K.M., Zhang, D.: Learning naive Bayes classifiers for music classification and retrieval. In: Proceedings of the ICPR, pp. 4589–4592 (2010) Fu, Z., Lu, G., Ting, K.M., Zhang, D.: Learning naive Bayes classifiers for music classification and retrieval. In: Proceedings of the ICPR, pp. 4589–4592 (2010)
122.
Zurück zum Zitat Fu, Z., Lu, G., Ting, K.M., Zhang, D.: On feature combination for music classification. In: Proceedings of the International Workshop on Structural and Syntactic Pattern Recognition, pp. 453–462 (2010) Fu, Z., Lu, G., Ting, K.M., Zhang, D.: On feature combination for music classification. In: Proceedings of the International Workshop on Structural and Syntactic Pattern Recognition, pp. 453–462 (2010)
123.
Zurück zum Zitat Fu, Z., Lu, G., Ting, K.M., Zhang, D.: A survey of audio-based music classification and annotation. IEEE Trans. Multimed. 13(2), 303–319 (2011) Fu, Z., Lu, G., Ting, K.M., Zhang, D.: A survey of audio-based music classification and annotation. IEEE Trans. Multimed. 13(2), 303–319 (2011)
124.
Zurück zum Zitat Fu, Z., Lu, G., Ting, K.M., Zhang, D.: Music classification via the bag-of-features approach. Pattern Recogn. Lett. 32(14), 1768–1777 (2011) Fu, Z., Lu, G., Ting, K.M., Zhang, D.: Music classification via the bag-of-features approach. Pattern Recogn. Lett. 32(14), 1768–1777 (2011)
125.
Zurück zum Zitat García, J., Hernández, E., Meng, A., Hansen, L.K., Larsen, J.: Discovering music structure via similarity fusion. In: Proceedings of the Music, Brain and Cognition Workshop (2007) García, J., Hernández, E., Meng, A., Hansen, L.K., Larsen, J.: Discovering music structure via similarity fusion. In: Proceedings of the Music, Brain and Cognition Workshop (2007)
126.
Zurück zum Zitat García-García, D., Arenas-García, J., Parrado-Hernandez, E., de Maria, F.D.: Music genre classification using the temporal structure of songs. In: IEEE International Workshop on Machine Learning for Signal Processing, Kittilä, Finland, Aug–Sept 2010 García-García, D., Arenas-García, J., Parrado-Hernandez, E., de Maria, F.D.: Music genre classification using the temporal structure of songs. In: IEEE International Workshop on Machine Learning for Signal Processing, Kittilä, Finland, Aug–Sept 2010
127.
Zurück zum Zitat García, A., Arenas, J., García, D., Parrado, E.: Music genre classification based on dynamical models. In: International Conference on Pattern Recognition Applications and Methods, pp. 250–256 (2012) García, A., Arenas, J., García, D., Parrado, E.: Music genre classification based on dynamical models. In: International Conference on Pattern Recognition Applications and Methods, pp. 250–256 (2012)
128.
Zurück zum Zitat Gedik, A.C., Alpkocak, A.: Instrument independent musical genre classification using random 3000 ms segment. In: Savacı, F.A. (ed.) TAINN 2005. LNCS (LNAI), vol. 3949, pp. 149–157. Springer, Heidelberg (2006) Gedik, A.C., Alpkocak, A.: Instrument independent musical genre classification using random 3000 ms segment. In: Savacı, F.A. (ed.) TAINN 2005. LNCS (LNAI), vol. 3949, pp. 149–157. Springer, Heidelberg (2006)
129.
Zurück zum Zitat Genussov, M., Cohen, I.: Musical genre classification of audio signals using geometric methods. In: Proceedings of the EUSIPCO, Aalborg, Denmark, pp. 497–501, Aug 2010 Genussov, M., Cohen, I.: Musical genre classification of audio signals using geometric methods. In: Proceedings of the EUSIPCO, Aalborg, Denmark, pp. 497–501, Aug 2010
130.
Zurück zum Zitat Ghosal, A., Chakraborty, R., Dhara, B., Saha, S.: Instrumental/song classification of music signal using RANSAC. In: Proceedings of the International Conference on Electronics Computer Technology, pp. 269–272, Apr 2011 Ghosal, A., Chakraborty, R., Dhara, B., Saha, S.: Instrumental/song classification of music signal using RANSAC. In: Proceedings of the International Conference on Electronics Computer Technology, pp. 269–272, Apr 2011
131.
Zurück zum Zitat Gjerdingen, R.O., Perrott, D.: Scanning the dial: the rapid recognition of music genres. J. New Music Res. 37(2), 93–100 (2008) Gjerdingen, R.O., Perrott, D.: Scanning the dial: the rapid recognition of music genres. J. New Music Res. 37(2), 93–100 (2008)
132.
Zurück zum Zitat Golub, S.: Classifying recorded music. Master’s thesis, University of Edinburgh, Edinburgh, Scotland, UK (2000) Golub, S.: Classifying recorded music. Master’s thesis, University of Edinburgh, Edinburgh, Scotland, UK (2000)
133.
Zurück zum Zitat Golzari, S., Doraisamy, S., Sulaiman, N., Udzir, N.I.: A hybrid approach to traditional Malay music genre classification: combining feature selection and artificial immune recognition system. In: Proceedings of the International Symposium on Information Technology, Aug 2008 Golzari, S., Doraisamy, S., Sulaiman, N., Udzir, N.I.: A hybrid approach to traditional Malay music genre classification: combining feature selection and artificial immune recognition system. In: Proceedings of the International Symposium on Information Technology, Aug 2008
134.
Zurück zum Zitat Golzari, S., Doraisamy, S., Sulaiman, M.N.B., Udzir, N.I., Norowi, N.M.: Artificial immune recognition system with nonlinear resource allocation method and application to traditional Malay music genre classification. In: Bentley, P.J., Lee, D., Jung, S. (eds.) ICARIS 2008. LNCS, vol. 5132, pp. 132–141. Springer, Heidelberg (2008) Golzari, S., Doraisamy, S., Sulaiman, M.N.B., Udzir, N.I., Norowi, N.M.: Artificial immune recognition system with nonlinear resource allocation method and application to traditional Malay music genre classification. In: Bentley, P.J., Lee, D., Jung, S. (eds.) ICARIS 2008. LNCS, vol. 5132, pp. 132–141. Springer, Heidelberg (2008)
135.
Zurück zum Zitat Golzari, S., Doraisamy, S., Norowi, N.M., Sulaiman, M.N., Udzir, N.I.: A comprehensive study in benchmarking feature selection and classification approaches for traditional Malay music genre classification. In: Proceedings of Data Mining, pp. 71–77, July 2008 Golzari, S., Doraisamy, S., Norowi, N.M., Sulaiman, M.N., Udzir, N.I.: A comprehensive study in benchmarking feature selection and classification approaches for traditional Malay music genre classification. In: Proceedings of Data Mining, pp. 71–77, July 2008
136.
Zurück zum Zitat González, A., Granados, A., Camacho, D., de Borja Rodríguez, F.: Influence of music representation on compression-based clustering. In: Proceedings of the IEEE Congress on Evolutionary Computation (2010) González, A., Granados, A., Camacho, D., de Borja Rodríguez, F.: Influence of music representation on compression-based clustering. In: Proceedings of the IEEE Congress on Evolutionary Computation (2010)
137.
Zurück zum Zitat Goulart, A.J.H., Maciel, C.D., Guido, R.C., Paulo, K.C.S., da Silva, I.N.: Music genre classification based on entropy and fractal lacunarity. In: IEEE International Symposium on Multimedia (2011) Goulart, A.J.H., Maciel, C.D., Guido, R.C., Paulo, K.C.S., da Silva, I.N.: Music genre classification based on entropy and fractal lacunarity. In: IEEE International Symposium on Multimedia (2011)
138.
Zurück zum Zitat Goulart, A., Guido, R., Maciel, C.: Exploring different approaches for music genre classification. Egypt. Inf. J. 13(2), 59–63 (2012) Goulart, A., Guido, R., Maciel, C.: Exploring different approaches for music genre classification. Egypt. Inf. J. 13(2), 59–63 (2012)
139.
Zurück zum Zitat Gouyon, F., Dixon, S., Pampalk, E., Widmer, G.: Evaluating rhythmic descriptors for musical genre classification. In: Proceedings of the International Audio Engineering Society Conference, pp. 196–204 (2004) Gouyon, F., Dixon, S., Pampalk, E., Widmer, G.: Evaluating rhythmic descriptors for musical genre classification. In: Proceedings of the International Audio Engineering Society Conference, pp. 196–204 (2004)
140.
Zurück zum Zitat Gouyon, F., Dixon, S.: Dance music classification: a tempo-based approach. In: Proceedings of the ISMIR, pp. 501–504 (2004) Gouyon, F., Dixon, S.: Dance music classification: a tempo-based approach. In: Proceedings of the ISMIR, pp. 501–504 (2004)
141.
Zurück zum Zitat Gouyon, F.: A computational approach to rhythm description – audio features for the computation of rhythm periodicity functions and their use in tempo induction and music content processing. Ph.D. thesis, Universitat Pompeu Fabra (2005) Gouyon, F.: A computational approach to rhythm description – audio features for the computation of rhythm periodicity functions and their use in tempo induction and music content processing. Ph.D. thesis, Universitat Pompeu Fabra (2005)
142.
Zurück zum Zitat Govaerts, S., Corthaut, N., Duval, E.: Using search engine for classification: does it still work? In: Proceedings of the IEEE International Symposium on Multimedia, pp. 483–488, Dec 2009 Govaerts, S., Corthaut, N., Duval, E.: Using search engine for classification: does it still work? In: Proceedings of the IEEE International Symposium on Multimedia, pp. 483–488, Dec 2009
143.
Zurück zum Zitat Grimaldi, M., Cunningham, P., Kokaram, A.: A wavelet packet representation of audio signals for music genre classification using different ensemble and feature selection techniques. In: Proceedings of the ACM Multimedia, pp. 102–108 (2003) Grimaldi, M., Cunningham, P., Kokaram, A.: A wavelet packet representation of audio signals for music genre classification using different ensemble and feature selection techniques. In: Proceedings of the ACM Multimedia, pp. 102–108 (2003)
144.
Zurück zum Zitat Grimaldi, M., Cunningham, P., Kokaram, A.: Discrete wavelet packet transform and ensembles of lazy and eager learners for music genre classification. Multimed. Syst. 11, 422–437 (2006) Grimaldi, M., Cunningham, P., Kokaram, A.: Discrete wavelet packet transform and ensembles of lazy and eager learners for music genre classification. Multimed. Syst. 11, 422–437 (2006)
145.
Zurück zum Zitat Grosse, R., Raina, R., Kwong, H., Ng, A.Y.: Shift-invariant sparse coding for audio classification. In: Proceedings of the Twenty-third Conference on Uncertainty in Artificial Intelligence (2007) Grosse, R., Raina, R., Kwong, H., Ng, A.Y.: Shift-invariant sparse coding for audio classification. In: Proceedings of the Twenty-third Conference on Uncertainty in Artificial Intelligence (2007)
146.
Zurück zum Zitat Guaus, E.: Audio content processing for automatic music genre classification: descriptors, databases, and classifiers. Ph.D. thesis, Universitat Pompeu Fabra, Barcelona, Spain (2009) Guaus, E.: Audio content processing for automatic music genre classification: descriptors, databases, and classifiers. Ph.D. thesis, Universitat Pompeu Fabra, Barcelona, Spain (2009)
147.
Zurück zum Zitat Hamel, P., Eck, D.: Learning features from music audio with deep belief networks. In: Proceedings of the ISMIR (2010) Hamel, P., Eck, D.: Learning features from music audio with deep belief networks. In: Proceedings of the ISMIR (2010)
148.
Zurück zum Zitat Han, K.P., Park, Y.S., Jeon, S.G., Lee, G.C., Ha, Y.H.: Genre classification system of TV sound signals based on a spectrogram analysis. IEEE Trans. Consumer Elect. 44(1), 33–42 (1998) Han, K.P., Park, Y.S., Jeon, S.G., Lee, G.C., Ha, Y.H.: Genre classification system of TV sound signals based on a spectrogram analysis. IEEE Trans. Consumer Elect. 44(1), 33–42 (1998)
149.
Zurück zum Zitat Hansen, L.K., Ahrendt, P., Larsen, J.: Towards cognitive component analysis. In: Proceedings of the International and Interdisciplinary Conference on Adaptive Knowledge Representation and Reasoning, Espoo, Finland, pp. 148–153, June 2005 Hansen, L.K., Ahrendt, P., Larsen, J.: Towards cognitive component analysis. In: Proceedings of the International and Interdisciplinary Conference on Adaptive Knowledge Representation and Reasoning, Espoo, Finland, pp. 148–153, June 2005
150.
Zurück zum Zitat Harb, H., Chen, L., Auloge, J.Y.: Mixture of experts for audio classification: an application to male female classification and musical genre recognition. In: Proceedings of the ICME (2004) Harb, H., Chen, L., Auloge, J.Y.: Mixture of experts for audio classification: an application to male female classification and musical genre recognition. In: Proceedings of the ICME (2004)
151.
Zurück zum Zitat Harb, H., Chen, L.: A general audio classifier based on human perception motivated model. Multimed. Tools Appl. 34, 375–395 (2007) Harb, H., Chen, L.: A general audio classifier based on human perception motivated model. Multimed. Tools Appl. 34, 375–395 (2007)
152.
Zurück zum Zitat Hartmann, K., Büchner, D., Berndt, A., Nürnberger, A., Lange, C.: Interactive data mining and machine learning techniques for musicology. In: Proceedings of the Conference on Interdisciplinary Musicology, pp. 1–8 (2007) Hartmann, K., Büchner, D., Berndt, A., Nürnberger, A., Lange, C.: Interactive data mining and machine learning techniques for musicology. In: Proceedings of the Conference on Interdisciplinary Musicology, pp. 1–8 (2007)
153.
Zurück zum Zitat Hartmann, M.A.: Testing a spectral-based feature set for audio genre classification. Master’s thesis, University of Jyväskylä, June 2011 Hartmann, M.A.: Testing a spectral-based feature set for audio genre classification. Master’s thesis, University of Jyväskylä, June 2011
154.
Zurück zum Zitat Heittola, T.: Automatic classification of music signals. Master’s thesis, Tampere University of Technology, Feb 2003 Heittola, T.: Automatic classification of music signals. Master’s thesis, Tampere University of Technology, Feb 2003
155.
Zurück zum Zitat Henaff, M., Jarrett, K., Kavukcuoglu, K., LeCun, Y.: Unsupervised learning of sparse features for scalable audio classification. In: Proceedings of the ISMIR, Miami, FL, Oct 2011 Henaff, M., Jarrett, K., Kavukcuoglu, K., LeCun, Y.: Unsupervised learning of sparse features for scalable audio classification. In: Proceedings of the ISMIR, Miami, FL, Oct 2011
156.
Zurück zum Zitat de la Higuera, C., Piat, F., Tantini, F.: Learning stochastic finite automata for musical style recognition. In: Farré, J., Litovsky, I., Schmitz, S. (eds.) CIAA 2005. LNCS, vol. 3845, pp. 345–346. Springer, Heidelberg (2006) de la Higuera, C., Piat, F., Tantini, F.: Learning stochastic finite automata for musical style recognition. In: Farré, J., Litovsky, I., Schmitz, S. (eds.) CIAA 2005. LNCS, vol. 3845, pp. 345–346. Springer, Heidelberg (2006)
157.
Zurück zum Zitat Hillewaere, R., Manderick, B., Conklin, D.: Global feature versus event models for folk song classification. In: Proceedings of the ISMIR, pp. 729–733 (2009) Hillewaere, R., Manderick, B., Conklin, D.: Global feature versus event models for folk song classification. In: Proceedings of the ISMIR, pp. 729–733 (2009)
158.
Zurück zum Zitat Hillewaere, R., Manderick, B., Conklin, D.: Melodic models for polyphonic music classification. In: Proceedings of the International Workshop on Machine Learning and Music (2009) Hillewaere, R., Manderick, B., Conklin, D.: Melodic models for polyphonic music classification. In: Proceedings of the International Workshop on Machine Learning and Music (2009)
159.
Zurück zum Zitat Hillewaere, R., Manderick, B., Conklin, D.: String quartet classification with monophonic models. In: Proceedings of the ISMIR, pp. 537–542 (2010) Hillewaere, R., Manderick, B., Conklin, D.: String quartet classification with monophonic models. In: Proceedings of the ISMIR, pp. 537–542 (2010)
160.
Zurück zum Zitat Hillewaere, R., Manderick, B., Conklin, D.: String methods for folk tune genre classification. In: Proceedings of the ISMIR (2012) Hillewaere, R., Manderick, B., Conklin, D.: String methods for folk tune genre classification. In: Proceedings of the ISMIR (2012)
161.
Zurück zum Zitat Holzapfel, A., Stylianou, Y.: A statistical approach to musical genre classification using non-negative matrix factorization. In: Proceedings of the ICASSP, pp. 693–696, Apr 2007 Holzapfel, A., Stylianou, Y.: A statistical approach to musical genre classification using non-negative matrix factorization. In: Proceedings of the ICASSP, pp. 693–696, Apr 2007
162.
Zurück zum Zitat Holzapfel, A., Stylianou, Y.: Musical genre classification using nonnegative matrix factorization-based features. IEEE Trans. Audio Speech Lang. Process. 16(2), 424–434 (2008) Holzapfel, A., Stylianou, Y.: Musical genre classification using nonnegative matrix factorization-based features. IEEE Trans. Audio Speech Lang. Process. 16(2), 424–434 (2008)
163.
Zurück zum Zitat Holzapfel, A., Stylianou, Y.: Rhythmic similarity of music based on dynamic periodicity warping. In: Proceedings of the ICASSP, pp. 2217–2220 (2008) Holzapfel, A., Stylianou, Y.: Rhythmic similarity of music based on dynamic periodicity warping. In: Proceedings of the ICASSP, pp. 2217–2220 (2008)
164.
Zurück zum Zitat Holzapfel, A., Stylianou, Y.: A scale based method for rhythmic similarity of music. In: Proceedings of the ICASSP, Taipei, Taiwan, pp. 317–320, Apr 2009 Holzapfel, A., Stylianou, Y.: A scale based method for rhythmic similarity of music. In: Proceedings of the ICASSP, Taipei, Taiwan, pp. 317–320, Apr 2009
165.
Zurück zum Zitat Homburg, H., Mierswa, I., Möller, B., Morik, K., Wurst, M.: A benchmark dataset for audio classification and clustering. In: Proceedings of the ISMIR, London, UK (2005) Homburg, H., Mierswa, I., Möller, B., Morik, K., Wurst, M.: A benchmark dataset for audio classification and clustering. In: Proceedings of the ISMIR, London, UK (2005)
166.
Zurück zum Zitat Honingh, A., Bod, R.: Clustering and classification of music by interval categories. In: Agon, C., Andreatta, M., Assayag, G., Amiot, E., Bresson, J., Mandereau, J. (eds.) MCM 2011. LNCS, vol. 6726, pp. 346–349. Springer, Heidelberg (2011) Honingh, A., Bod, R.: Clustering and classification of music by interval categories. In: Agon, C., Andreatta, M., Assayag, G., Amiot, E., Bresson, J., Mandereau, J. (eds.) MCM 2011. LNCS, vol. 6726, pp. 346–349. Springer, Heidelberg (2011)
167.
Zurück zum Zitat Hsieh, C.T., Han, C.C., Lee, C.H., Fan, K.C.: Pattern classification using eigenspace projection. In: Proceedings of the International Conference on Intelligent Information Hiding and Multimedia Signal Processing, pp. 154–157, July 2012 Hsieh, C.T., Han, C.C., Lee, C.H., Fan, K.C.: Pattern classification using eigenspace projection. In: Proceedings of the International Conference on Intelligent Information Hiding and Multimedia Signal Processing, pp. 154–157, July 2012
168.
Zurück zum Zitat Hu, Y., Ogihara, M.: Genre classification for million song dataset using confidence-based classifiers combination. In: Proceedings of the ACM SIGIR, pp. 1083–1084. ACM, New York (2012) Hu, Y., Ogihara, M.: Genre classification for million song dataset using confidence-based classifiers combination. In: Proceedings of the ACM SIGIR, pp. 1083–1084. ACM, New York (2012)
169.
Zurück zum Zitat Iñesta, J.M., Ponce de León, P.J., Heredia, J.L.: A ground-truth experiment on melody genre recognition in absence of timbre. In: Proceedings of the International Conference on Music Perception and Cognition, pp. 758–761 (2009) Iñesta, J.M., Ponce de León, P.J., Heredia, J.L.: A ground-truth experiment on melody genre recognition in absence of timbre. In: Proceedings of the International Conference on Music Perception and Cognition, pp. 758–761 (2009)
172.
Zurück zum Zitat Jang, D., Jin, M., Yoo, C.D.: Music genre classification using novel features and a weighted voting method. In: Proceedings of the ICME, pp. 1377–1380 (2008) Jang, D., Jin, M., Yoo, C.D.: Music genre classification using novel features and a weighted voting method. In: Proceedings of the ICME, pp. 1377–1380 (2008)
173.
Zurück zum Zitat Jennings, H., Ivanov, P., Martins, A., da Silva, P., Viswanathan, G.: Variance fluctuations in nonstationary time series: a comparative study of music genres. Phys. A: Stat. Theor. Phys. 336(3–4), 585–594 (2004) Jennings, H., Ivanov, P., Martins, A., da Silva, P., Viswanathan, G.: Variance fluctuations in nonstationary time series: a comparative study of music genres. Phys. A: Stat. Theor. Phys. 336(3–4), 585–594 (2004)
174.
Zurück zum Zitat Jensen, J., Christensen, M., Murthi, M., Jensen, S.: Evaluation of MFCC estimation techniques for music similarity. In: Proceedings of the EUSIPCO (2006) Jensen, J., Christensen, M., Murthi, M., Jensen, S.: Evaluation of MFCC estimation techniques for music similarity. In: Proceedings of the EUSIPCO (2006)
175.
Zurück zum Zitat Jensen, K.: Music genre classification using an auditory memory model. In: Ystad, S., Aramaki, M., Kronland-Martinet, R., Jensen, K., Mohanty, S. (eds.) CMMR and FRSM 2011. LNCS, vol. 7172, pp. 79–88. Springer, Heidelberg (2012) Jensen, K.: Music genre classification using an auditory memory model. In: Ystad, S., Aramaki, M., Kronland-Martinet, R., Jensen, K., Mohanty, S. (eds.) CMMR and FRSM 2011. LNCS, vol. 7172, pp. 79–88. Springer, Heidelberg (2012)
176.
Zurück zum Zitat Jiang, D.N., L.-Lu, Zhang, H.J., Tao, J.H., Cai, L.H.: Music type classification by spectral contrast features. In: Proceedings of the ICME (2002) Jiang, D.N., L.-Lu, Zhang, H.J., Tao, J.H., Cai, L.H.: Music type classification by spectral contrast features. In: Proceedings of the ICME (2002)
177.
Zurück zum Zitat Jin, X., Bie, R.: Random forest and PCA for self-organizing maps based automatic music genre discrimination. In: Proceedings of the Data Mining, pp. 414–417 (2006) Jin, X., Bie, R.: Random forest and PCA for self-organizing maps based automatic music genre discrimination. In: Proceedings of the Data Mining, pp. 414–417 (2006)
178.
Zurück zum Zitat Lu, J., Wan, W., Yu, X., Li, C.: Music style classification using support vector machine. In: Proceedings of the International Conference on Wireless Communication and Mobile Computing, pp. 452–455, Dec 2009 Lu, J., Wan, W., Yu, X., Li, C.: Music style classification using support vector machine. In: Proceedings of the International Conference on Wireless Communication and Mobile Computing, pp. 452–455, Dec 2009
179.
Zurück zum Zitat Jothilakshmi, S., Kathiresan, N.: Automatic music genre classification for Indian music. In: Proceedings of the International Conference on Software and Computer Applications (2012) Jothilakshmi, S., Kathiresan, N.: Automatic music genre classification for Indian music. In: Proceedings of the International Conference on Software and Computer Applications (2012)
180.
Zurück zum Zitat Ju, H., Xu, J.X., VanDongen, A.M.J.: Classification of musical styles using liquid state machines. In: Proceedings of the International Joint Conference on Neural Networks, pp. 1–7 (2010) Ju, H., Xu, J.X., VanDongen, A.M.J.: Classification of musical styles using liquid state machines. In: Proceedings of the International Joint Conference on Neural Networks, pp. 1–7 (2010)
181.
Zurück zum Zitat Kaminskas, M., Ricci, F.: Contextual music information retrieval and recommendation: state of the art and challenges. Comput. Sci. Rev. 6(2–3), 89–119 (2012)MATH Kaminskas, M., Ricci, F.: Contextual music information retrieval and recommendation: state of the art and challenges. Comput. Sci. Rev. 6(2–3), 89–119 (2012)MATH
182.
Zurück zum Zitat Karkavitsas, G.V., Tsihrintzis, G.A.: Automatic music genre classification using hybrid genetic algorithms. In: Tsihrintzis, G.A., Virvou, M., Jain, L.C., Howlett, R.J. (eds.) IIMSS 2011. SIST, vol. 11, pp. 323–335. Springer, Heidelberg (2011) Karkavitsas, G.V., Tsihrintzis, G.A.: Automatic music genre classification using hybrid genetic algorithms. In: Tsihrintzis, G.A., Virvou, M., Jain, L.C., Howlett, R.J. (eds.) IIMSS 2011. SIST, vol. 11, pp. 323–335. Springer, Heidelberg (2011)
183.
Zurück zum Zitat Karkavitsas, G.V., Tsihrintzis, G.A.: Optimization of an automatic music genre classification system via hyper-entities. In: Proceedings of the International Conference on Intelligent Information Hiding and Multimedia Signal Processing, pp. 449–452 (2012) Karkavitsas, G.V., Tsihrintzis, G.A.: Optimization of an automatic music genre classification system via hyper-entities. In: Proceedings of the International Conference on Intelligent Information Hiding and Multimedia Signal Processing, pp. 449–452 (2012)
184.
Zurück zum Zitat Karydis, I.: Symbolic music genre classification based on note pitch and duration. In: Manolopoulos, Y., Pokorný, J., Sellis, T.K. (eds.) ADBIS 2006. LNCS, vol. 4152, pp. 329–338. Springer, Heidelberg (2006) Karydis, I.: Symbolic music genre classification based on note pitch and duration. In: Manolopoulos, Y., Pokorný, J., Sellis, T.K. (eds.) ADBIS 2006. LNCS, vol. 4152, pp. 329–338. Springer, Heidelberg (2006)
185.
Zurück zum Zitat Karydis, I., Nanopoulos, A., Manolopoulos, Y.: Symbolic musical genre classification based on repeating patterns. In: Proceedings of the ACM Workshop on Audio and Music Computing Multimedia, pp. 53–58 (2006) Karydis, I., Nanopoulos, A., Manolopoulos, Y.: Symbolic musical genre classification based on repeating patterns. In: Proceedings of the ACM Workshop on Audio and Music Computing Multimedia, pp. 53–58 (2006)
186.
Zurück zum Zitat Kim, H.G., Cho, J.M.: Car audio equalizer system using music classification and loudness compensation. In: Proceedings of the International Conference on ICT Convergence (2011) Kim, H.G., Cho, J.M.: Car audio equalizer system using music classification and loudness compensation. In: Proceedings of the International Conference on ICT Convergence (2011)
187.
Zurück zum Zitat Kini, S., Gulati, S., Rao, P.: Automatic genre classification of North Indian devotional music. In: National Conference on Communications (2011) Kini, S., Gulati, S., Rao, P.: Automatic genre classification of North Indian devotional music. In: National Conference on Communications (2011)
188.
Zurück zum Zitat Kirss, P.: Audio based genre classification of electronic music. Master’s thesis, University of Jyväskylä, June 2007 Kirss, P.: Audio based genre classification of electronic music. Master’s thesis, University of Jyväskylä, June 2007
189.
Zurück zum Zitat Kitahara, T., Tsuchihashi, Y., Katayose, H.: Music genre classification and similarity calculation using bass-line features. In: Proceedings of the IEEE International Symposium on Multimedia, pp. 574–579, Dec 2008 Kitahara, T., Tsuchihashi, Y., Katayose, H.: Music genre classification and similarity calculation using bass-line features. In: Proceedings of the IEEE International Symposium on Multimedia, pp. 574–579, Dec 2008
190.
Zurück zum Zitat Kobayakawa, M., Hoshi, M.: Musical genre classification of MPEG-4 Twin VQ audio data. In: Proceedings of the ICME (2011) Kobayakawa, M., Hoshi, M.: Musical genre classification of MPEG-4 Twin VQ audio data. In: Proceedings of the ICME (2011)
191.
Zurück zum Zitat Koerich, A., Poitevin, C.: Combination of homogeneous classifiers for musical genre classification. In: IEEE International Conference on Systems, Man and Cybernetics, Oct 2005 Koerich, A., Poitevin, C.: Combination of homogeneous classifiers for musical genre classification. In: IEEE International Conference on Systems, Man and Cybernetics, Oct 2005
192.
Zurück zum Zitat Kofod, C., Ortiz-Arroyo, D.: Exploring the design space of symbolic music genre classification using data mining techniques. In: Proceedings of the International Conference on Computational Intelligence for Modelling, Control and Automation, pp. 432–448, Dec 2008 Kofod, C., Ortiz-Arroyo, D.: Exploring the design space of symbolic music genre classification using data mining techniques. In: Proceedings of the International Conference on Computational Intelligence for Modelling, Control and Automation, pp. 432–448, Dec 2008
193.
Zurück zum Zitat Kosina, K.: Music genre recognition. Master’s thesis, Hagenberg Technical University, Hagenberg, Germany, June 2002 Kosina, K.: Music genre recognition. Master’s thesis, Hagenberg Technical University, Hagenberg, Germany, June 2002
194.
Zurück zum Zitat Kostek, B., Kupryjanow, A., Zwan, P., Jiang, W., Raś, Z.W., Wojnarski, M., Swietlicka, J.: Report of the ISMIS 2011 contest: music information retrieval. In: Kryszkiewicz, M., Rybinski, H., Skowron, A., Raś, Z.W. (eds.) ISMIS 2011. LNCS, vol. 6804, pp. 715–724. Springer, Heidelberg (2011) Kostek, B., Kupryjanow, A., Zwan, P., Jiang, W., Raś, Z.W., Wojnarski, M., Swietlicka, J.: Report of the ISMIS 2011 contest: music information retrieval. In: Kryszkiewicz, M., Rybinski, H., Skowron, A., Raś, Z.W. (eds.) ISMIS 2011. LNCS, vol. 6804, pp. 715–724. Springer, Heidelberg (2011)
195.
Zurück zum Zitat Kotropoulos, C., Arce, G.R., Panagakis, Y.: Ensemble discriminant sparse projections applied to music genre classification. In: Proceedings of the ICPR, pp. 823–825, Aug 2010 Kotropoulos, C., Arce, G.R., Panagakis, Y.: Ensemble discriminant sparse projections applied to music genre classification. In: Proceedings of the ICPR, pp. 823–825, Aug 2010
196.
Zurück zum Zitat van Kranenburg, P., Baker, W.: Musical style recognition - a quantitative approach. In: Proceedings of the Conference on Interdisciplinary Musicology (2004) van Kranenburg, P., Baker, W.: Musical style recognition - a quantitative approach. In: Proceedings of the Conference on Interdisciplinary Musicology (2004)
197.
Zurück zum Zitat van Kranenburg, P.: On measuring musical style - the case of some disputed organ fugues in the J.S. Bach (BWV)catalogue. Computing In Musicology (2007-8) van Kranenburg, P.: On measuring musical style - the case of some disputed organ fugues in the J.S. Bach (BWV)catalogue. Computing In Musicology (2007-8)
198.
Zurück zum Zitat van Kranenburg, P., Garbers, J., Volk, A., Wiering, F., Grijp, L., Veltkamp, R.: Collaboration perspectives for folk song research and music information retrieval: the indispensable role of computational musicology. J. Interdiscipl. Music Stud. 4(1), 17–43 (2010) van Kranenburg, P., Garbers, J., Volk, A., Wiering, F., Grijp, L., Veltkamp, R.: Collaboration perspectives for folk song research and music information retrieval: the indispensable role of computational musicology. J. Interdiscipl. Music Stud. 4(1), 17–43 (2010)
199.
Zurück zum Zitat van Kranenburg, P., Volk, A., Wiering, F.: A comparison between global and local features for computational classification of folk song melodies. J. New Music Res. 42, 1–18 (2012) van Kranenburg, P., Volk, A., Wiering, F.: A comparison between global and local features for computational classification of folk song melodies. J. New Music Res. 42, 1–18 (2012)
200.
Zurück zum Zitat Krasser, J., Abeßer, J., Großmann, H., Dittmar, C., Cano, E.: Improved music similarity computation based on tone objects. In: Proceedings of the Audio Mostly Conference, pp. 47–54 (2012) Krasser, J., Abeßer, J., Großmann, H., Dittmar, C., Cano, E.: Improved music similarity computation based on tone objects. In: Proceedings of the Audio Mostly Conference, pp. 47–54 (2012)
201.
Zurück zum Zitat Krumhansl, C.L.: Plink: “thin slices” of music. Music Percept.: Interdiscipl. J. 27(5), 337–354 (2010) Krumhansl, C.L.: Plink: “thin slices” of music. Music Percept.: Interdiscipl. J. 27(5), 337–354 (2010)
202.
Zurück zum Zitat Kuo, F.F., Shan, M.K.: A personalized music filtering system based on melody style classification. In: Proceedings of the IEEE International Conference on Data Mining, pp. 649–652 (2002) Kuo, F.F., Shan, M.K.: A personalized music filtering system based on melody style classification. In: Proceedings of the IEEE International Conference on Data Mining, pp. 649–652 (2002)
203.
Zurück zum Zitat Kuo, F.F., Shan, M.K.: Looking for new, not known music only: music retrieval by melody style. In: Proceedings of the Joint ACM/IEEE Conference on Digital Libraries, pp. 243–251, June 2004 Kuo, F.F., Shan, M.K.: Looking for new, not known music only: music retrieval by melody style. In: Proceedings of the Joint ACM/IEEE Conference on Digital Libraries, pp. 243–251, June 2004
204.
Zurück zum Zitat Lambrou, T., Kudumakis, P., Speller, R., Sandler, M., Linney, A.: Classification of audio signals using statistical features on time and wavelet transform domains. In: Proceedings of the ICASSP, pp. 3621–3624, May 1998 Lambrou, T., Kudumakis, P., Speller, R., Sandler, M., Linney, A.: Classification of audio signals using statistical features on time and wavelet transform domains. In: Proceedings of the ICASSP, pp. 3621–3624, May 1998
205.
Zurück zum Zitat Lampropoulos, A.S., Lampropoulou, P.S., Tsihrintzis, G.A.: Musical genre classification enhanced by improved source separation techniques. In: Proceedings of the ISMIR (2005) Lampropoulos, A.S., Lampropoulou, P.S., Tsihrintzis, G.A.: Musical genre classification enhanced by improved source separation techniques. In: Proceedings of the ISMIR (2005)
206.
Zurück zum Zitat Lampropoulos, A.S., Lampropoulou, P.S., Tsihrintzis, G.A.: Music genre classification based on ensemble of signals produced by source separation methods. Intell. Dec. Technol. 4(3), 229–237 (2010) Lampropoulos, A.S., Lampropoulou, P.S., Tsihrintzis, G.A.: Music genre classification based on ensemble of signals produced by source separation methods. Intell. Dec. Technol. 4(3), 229–237 (2010)
207.
Zurück zum Zitat Lampropoulos, A., Lampropoulou, P., Tsihrintzis, G.: A cascade-hybrid music recommender system for mobile services based on musical genre classification and personality diagnosis. Multimed. Tools Appl. 59, 241–258 (2012) Lampropoulos, A., Lampropoulou, P., Tsihrintzis, G.: A cascade-hybrid music recommender system for mobile services based on musical genre classification and personality diagnosis. Multimed. Tools Appl. 59, 241–258 (2012)
208.
Zurück zum Zitat Langlois, T., Marques, G.: A music classification method based on timbral features. In: Proceedings of the ISMIR (2009) Langlois, T., Marques, G.: A music classification method based on timbral features. In: Proceedings of the ISMIR (2009)
209.
Zurück zum Zitat Langlois, T., Marques, G.: Automatic music genre classification using a hierarchical clustering and a language model approach. In: Proceedings of the International Conference on Advances in Multimedia (2009) Langlois, T., Marques, G.: Automatic music genre classification using a hierarchical clustering and a language model approach. In: Proceedings of the International Conference on Advances in Multimedia (2009)
210.
Zurück zum Zitat Lee, J.-W., Park, S.-B., Kim, S.-K.: Music genre classification using a time-delay neural network. In: Wang, J., Yi, Z., Żurada, J.M., Lu, B.-L., Yin, H. (eds.) ISNN 2006. LNCS, vol. 3972, pp. 178–187. Springer, Heidelberg (2006) Lee, J.-W., Park, S.-B., Kim, S.-K.: Music genre classification using a time-delay neural network. In: Wang, J., Yi, Z., Żurada, J.M., Lu, B.-L., Yin, H. (eds.) ISNN 2006. LNCS, vol. 3972, pp. 178–187. Springer, Heidelberg (2006)
211.
Zurück zum Zitat Lee, C.H., Shih, J.L., Yu, K.M., Su, J.M.: Automatic music genre classification using modulation spectral contrast feature. In: Proceedings of the ICME (2007) Lee, C.H., Shih, J.L., Yu, K.M., Su, J.M.: Automatic music genre classification using modulation spectral contrast feature. In: Proceedings of the ICME (2007)
212.
Zurück zum Zitat Lee, C.H., Shih, J.L., Yu, K.M., Lin, H.S., Wei, M.H.: Fusion of static and transitional information of cepstral and spectral features for music genre classification. In: IEEE Asia-Pacific Service Computing Conference (2008) Lee, C.H., Shih, J.L., Yu, K.M., Lin, H.S., Wei, M.H.: Fusion of static and transitional information of cepstral and spectral features for music genre classification. In: IEEE Asia-Pacific Service Computing Conference (2008)
213.
Zurück zum Zitat Lee, C.H., Lin, H.S., Chou, C.H., Shih, J.L.: Modulation spectral analysis of static and transitional information of cepstral and spectral features for music genre classification. In: Proceedings of the International Conference on Intelligent Information Hiding and Multimedia Signal Processing (2009) Lee, C.H., Lin, H.S., Chou, C.H., Shih, J.L.: Modulation spectral analysis of static and transitional information of cepstral and spectral features for music genre classification. In: Proceedings of the International Conference on Intelligent Information Hiding and Multimedia Signal Processing (2009)
214.
Zurück zum Zitat Lee, C., Shih, J., Yu, K., Lin, H.: Automatic music genre classification based on modulation spectral analysis of spectral and cepstral features. IEEE Trans. Multimed. 11(4), 670–682 (2009) Lee, C., Shih, J., Yu, K., Lin, H.: Automatic music genre classification based on modulation spectral analysis of spectral and cepstral features. IEEE Trans. Multimed. 11(4), 670–682 (2009)
215.
Zurück zum Zitat Lee, H., Largman, Y., Pham, P., Ng, A.Y.: Unsupervised feature learning for audio classification using convolutional deep belief networks. In: Proceedings of the Neural Information Processing Systems, Vancouver, BC, Canada, Dec 2009 Lee, H., Largman, Y., Pham, P., Ng, A.Y.: Unsupervised feature learning for audio classification using convolutional deep belief networks. In: Proceedings of the Neural Information Processing Systems, Vancouver, BC, Canada, Dec 2009
216.
Zurück zum Zitat Lee, C.H., Chou, C.H., Lien, C.C., Fang, J.C.: Music genre classification using modulation spectral features and multiple prototype vectors representation. In: International Congress on Image and Signal Processing (2011) Lee, C.H., Chou, C.H., Lien, C.C., Fang, J.C.: Music genre classification using modulation spectral features and multiple prototype vectors representation. In: International Congress on Image and Signal Processing (2011)
217.
Zurück zum Zitat Lehn-Schioler, T., Arenas-García, J., Petersen, K.B., Hansen, L.: A genre classification plug-in for data collection. In: Proceedings of the ISMIR (2006) Lehn-Schioler, T., Arenas-García, J., Petersen, K.B., Hansen, L.: A genre classification plug-in for data collection. In: Proceedings of the ISMIR (2006)
218.
Zurück zum Zitat de León, P., Iñesta, J.: Musical style identification using self-organising maps. In: Proceedings of the WEDELMUSIC, pp. 82–89 (2002) de León, P., Iñesta, J.: Musical style identification using self-organising maps. In: Proceedings of the WEDELMUSIC, pp. 82–89 (2002)
219.
Zurück zum Zitat de León, P., Iñesta, J.: Feature-driven recognition of music styles. In: Perales, F.J., Campilho, A.C., Pérez, N., Sanfeliu, A. (eds.) IbPRIA 2003. LNCS, vol. 2652, pp. 773–781. Springer, Heidelberg (2003) de León, P., Iñesta, J.: Feature-driven recognition of music styles. In: Perales, F.J., Campilho, A.C., Pérez, N., Sanfeliu, A. (eds.) IbPRIA 2003. LNCS, vol. 2652, pp. 773–781. Springer, Heidelberg (2003)
220.
Zurück zum Zitat de León, P.J.P., Iñesta, J.M.: Musical style classification from symbolic data: a two-styles case study. In: Wiil, U.K. (ed.) CMMR 2003. LNCS, vol. 2771, pp. 167–178. Springer, Heidelberg (2004) de León, P.J.P., Iñesta, J.M.: Musical style classification from symbolic data: a two-styles case study. In: Wiil, U.K. (ed.) CMMR 2003. LNCS, vol. 2771, pp. 167–178. Springer, Heidelberg (2004)
221.
Zurück zum Zitat de León, P.P., Iñesta, J.: Pattern recognition approach for music style identification using shallow statistical descriptors. IEEE Trans. Syst. Man Cybern.: Part C: Appl. Rev. 37(2), 248–257 (2007). de León, P.P., Iñesta, J.: Pattern recognition approach for music style identification using shallow statistical descriptors. IEEE Trans. Syst. Man Cybern.: Part C: Appl. Rev. 37(2), 248–257 (2007).
222.
Zurück zum Zitat de León, F., Martinez, K.: Enhancing timbre model using MFCC and its time derivatives for music similarity estimation. In: Proceedings of the EUSIPCO, Bucharest, Romania, pp. 2005–2009, Aug 2012 de León, F., Martinez, K.: Enhancing timbre model using MFCC and its time derivatives for music similarity estimation. In: Proceedings of the EUSIPCO, Bucharest, Romania, pp. 2005–2009, Aug 2012
223.
Zurück zum Zitat de León, F., Martinez, K.: Towards efficient music genre classification using FastMap. In: Proceedings of the DAFx (2012) de León, F., Martinez, K.: Towards efficient music genre classification using FastMap. In: Proceedings of the DAFx (2012)
224.
Zurück zum Zitat Lerch, A.: An Introduction to Audio Content Analysis: Applications in Signal Processing and Music Informatics. Wiley/IEEE Press, Hoboken (2012) Lerch, A.: An Introduction to Audio Content Analysis: Applications in Signal Processing and Music Informatics. Wiley/IEEE Press, Hoboken (2012)
225.
Zurück zum Zitat Levy, M., Sandler, M.: Lightweight measures for timbral similarity of musical audio. In: Proceedings of the ACM Workshop on Audio and Music Computing Multimedia, pp. 27–36 (2006) Levy, M., Sandler, M.: Lightweight measures for timbral similarity of musical audio. In: Proceedings of the ACM Workshop on Audio and Music Computing Multimedia, pp. 27–36 (2006)
226.
Zurück zum Zitat Li, T., Ogihara, M., Li, Q.: A comparative study on content-based music genre classification. In: Proceedings of the International ACM SIGIR Conference on Research and Development in Information Retrieval (2003) Li, T., Ogihara, M., Li, Q.: A comparative study on content-based music genre classification. In: Proceedings of the International ACM SIGIR Conference on Research and Development in Information Retrieval (2003)
227.
Zurück zum Zitat Li, T., Tzanetakis, G.: Factors in automatic musical genre classification of audio signals. In: Proceedings of the IEEE Workshop on Applications of the Signal Processing to Audio and Acoustics (2003) Li, T., Tzanetakis, G.: Factors in automatic musical genre classification of audio signals. In: Proceedings of the IEEE Workshop on Applications of the Signal Processing to Audio and Acoustics (2003)
228.
Zurück zum Zitat Li, T., Ogihara, M.: Music artist style identification by semi-supervised learning from both lyrics and contents. In: Proceedings of the ACM Multimedia (2004) Li, T., Ogihara, M.: Music artist style identification by semi-supervised learning from both lyrics and contents. In: Proceedings of the ACM Multimedia (2004)
229.
Zurück zum Zitat Li, M., Sleep, R.: Melody classification using a similarity metric based on Kolmogorov complexity. In: Proceedings of the SMC (2004) Li, M., Sleep, R.: Melody classification using a similarity metric based on Kolmogorov complexity. In: Proceedings of the SMC (2004)
230.
Zurück zum Zitat Li, M., Sleep, R.: Genre classification via an LZ78-based string kernel. In: Proceedings of the ISMIR (2005) Li, M., Sleep, R.: Genre classification via an LZ78-based string kernel. In: Proceedings of the ISMIR (2005)
231.
Zurück zum Zitat Li, T., Ogihara, M.: Music genre classification with taxonomy. In: Proceedings of the ICASSP, Philadelphia, PA, pp. 197–200, Mar 2005 Li, T., Ogihara, M.: Music genre classification with taxonomy. In: Proceedings of the ICASSP, Philadelphia, PA, pp. 197–200, Mar 2005
232.
Zurück zum Zitat Li, T., Ogihara, M.: Toward intelligent music information retrieval. IEEE Trans. Multimed. 8(3), 564–574 (2006) Li, T., Ogihara, M.: Toward intelligent music information retrieval. IEEE Trans. Multimed. 8(3), 564–574 (2006)
233.
Zurück zum Zitat Li, T., Ogihara, M., Shao, B., Wang, D.: Machine learning approaches for music information retrieval. In: Theory and Novel Applications of Machine Learning. I-Tech, Austria (2009) Li, T., Ogihara, M., Shao, B., Wang, D.: Machine learning approaches for music information retrieval. In: Theory and Novel Applications of Machine Learning. I-Tech, Austria (2009)
234.
Zurück zum Zitat Li, T.L., Chan, A.B., Chun, A.H.: Automatic musical pattern feature extraction using convolutional neural network. In: Proceedings of the International Conference on Data Mining and Applications (2010) Li, T.L., Chan, A.B., Chun, A.H.: Automatic musical pattern feature extraction using convolutional neural network. In: Proceedings of the International Conference on Data Mining and Applications (2010)
235.
Zurück zum Zitat Li, T., Chan, A.: Genre classification and the invariance of MFCC features to key and tempo. In: Proceedings of the International Conference on Multimedia Modeling, Taipei, China, Jan 2011 Li, T., Chan, A.: Genre classification and the invariance of MFCC features to key and tempo. In: Proceedings of the International Conference on Multimedia Modeling, Taipei, China, Jan 2011
236.
Zurück zum Zitat Lidy, T., Rauber, A.: Genre-oriented organization of music collections using the SOMeJB system: an analysis of rhythm patterns and other features. In: Proceedings of the DELOS Workshop Multimedia Contents in Digital Libraries (2003) Lidy, T., Rauber, A.: Genre-oriented organization of music collections using the SOMeJB system: an analysis of rhythm patterns and other features. In: Proceedings of the DELOS Workshop Multimedia Contents in Digital Libraries (2003)
237.
Zurück zum Zitat Lidy, T.: Marsyas and rhythm patterns: evaluation of two music genre classification systems. In: Proceedings of the Workshop Data Analysis, June 2003 Lidy, T.: Marsyas and rhythm patterns: evaluation of two music genre classification systems. In: Proceedings of the Workshop Data Analysis, June 2003
238.
Zurück zum Zitat Lidy, T., Rauber, A.: Evaluation of feature extractors and psycho-acoustic transformations for music genre classification. In: Proceedings of the ISMIR (2005) Lidy, T., Rauber, A.: Evaluation of feature extractors and psycho-acoustic transformations for music genre classification. In: Proceedings of the ISMIR (2005)
239.
Zurück zum Zitat Lidy, T.: Evaluation of new audio features and their utilization in novel music retrieval applications. Master’s thesis, Vienna University of Technology, Dec 2006 Lidy, T.: Evaluation of new audio features and their utilization in novel music retrieval applications. Master’s thesis, Vienna University of Technology, Dec 2006
240.
Zurück zum Zitat Lidy, T., Rauber, A., Pertusa, A., Iñesta, J.M.: Improving genre classification by combination of audio and symbolic descriptors using a transcription system. In: Proceedings of the ISMIR, Vienna, Austria, pp. 61–66, Sept 2007 Lidy, T., Rauber, A., Pertusa, A., Iñesta, J.M.: Improving genre classification by combination of audio and symbolic descriptors using a transcription system. In: Proceedings of the ISMIR, Vienna, Austria, pp. 61–66, Sept 2007
241.
Zurück zum Zitat Lidy, T., Rauber, A.: Classification and clustering of music for novel music access applications. In: Cord, M., Cunningham, P. (eds.) Machine Learning Techniques for Multimedia, pp. 249–285. Springer, Heidelberg (2008) Lidy, T., Rauber, A.: Classification and clustering of music for novel music access applications. In: Cord, M., Cunningham, P. (eds.) Machine Learning Techniques for Multimedia, pp. 249–285. Springer, Heidelberg (2008)
242.
Zurück zum Zitat Lidy, T., Silla, C., Cornelis, O., Gouyon, F., Rauber, A., Kaestner, C.A., Koerich, A.L.: On the suitability of state-of-the-art music information retrieval methods for analyzing, categorizing and accessing non-western and ethnic music collections. Signal Process. 90(4), 1032–1048 (2010)MATH Lidy, T., Silla, C., Cornelis, O., Gouyon, F., Rauber, A., Kaestner, C.A., Koerich, A.L.: On the suitability of state-of-the-art music information retrieval methods for analyzing, categorizing and accessing non-western and ethnic music collections. Signal Process. 90(4), 1032–1048 (2010)MATH
243.
Zurück zum Zitat Lidy, T., Mayer, R., Rauber, A., de León, P.P., Pertusa, A., Quereda, J.: A cartesian ensemble of feature subspace classifiers for music categorization. In: Proceedings of the ISMIR, pp. 279–284 (2010) Lidy, T., Mayer, R., Rauber, A., de León, P.P., Pertusa, A., Quereda, J.: A cartesian ensemble of feature subspace classifiers for music categorization. In: Proceedings of the ISMIR, pp. 279–284 (2010)
244.
Zurück zum Zitat Lim, S.C., Jang, S.J., Lee, S.P., Kim, M.Y.: Music genre/mood classification using a feature-based modulation spectrum. In: Proceedings of the International Conference on Modelling, Identification and Control (2011) Lim, S.C., Jang, S.J., Lee, S.P., Kim, M.Y.: Music genre/mood classification using a feature-based modulation spectrum. In: Proceedings of the International Conference on Modelling, Identification and Control (2011)
245.
Zurück zum Zitat Lin, C.-R., Liu, N.-H., Wu, Y.-H., Chen, A.L.P.: Music classification using significant repeating patterns. In: Lee, Y.J., Li, J., Whang, K.-Y., Lee, D. (eds.) DASFAA 2004. LNCS, vol. 2973, pp. 506–518. Springer, Heidelberg (2004) Lin, C.-R., Liu, N.-H., Wu, Y.-H., Chen, A.L.P.: Music classification using significant repeating patterns. In: Lee, Y.J., Li, J., Whang, K.-Y., Lee, D. (eds.) DASFAA 2004. LNCS, vol. 2973, pp. 506–518. Springer, Heidelberg (2004)
246.
Zurück zum Zitat Lippens, S., Martens, J., De Mulder, T.: A comparison of human and automatic musical genre classification. In: Proceedings of the ICASSP, pp. 233–236, May 2004 Lippens, S., Martens, J., De Mulder, T.: A comparison of human and automatic musical genre classification. In: Proceedings of the ICASSP, pp. 233–236, May 2004
247.
Zurück zum Zitat Liu, Y., Xu, J., Wei, L., Tian, Y.: The study of the classification of Chinese folk songs by regional style. In: Proceedings of the International Conference on Semantic Computing, pp. 657–662, Sept 2007 Liu, Y., Xu, J., Wei, L., Tian, Y.: The study of the classification of Chinese folk songs by regional style. In: Proceedings of the International Conference on Semantic Computing, pp. 657–662, Sept 2007
248.
Zurück zum Zitat Liu, X., Yang, D., Chen, X.: New approach to classification of Chinese folk music based on extension of hmm. In: Proceedings of the ICALIP, pp. 1172–1179, July 2008 Liu, X., Yang, D., Chen, X.: New approach to classification of Chinese folk music based on extension of hmm. In: Proceedings of the ICALIP, pp. 1172–1179, July 2008
249.
Zurück zum Zitat Liu, Y., Wei, L., Wang, P.: Regional style automatic identification for Chinese folk songs. In: World Congress on Computer Science and Information Engineering (2009) Liu, Y., Wei, L., Wang, P.: Regional style automatic identification for Chinese folk songs. In: World Congress on Computer Science and Information Engineering (2009)
250.
Zurück zum Zitat Liu, Y., Xiang, Q., Wang, Y., Cai, L.: Cultural style based music classification of audio signals. In: Proceedings of the ICASSP, Taipei, Taiwan, Apr 2009 Liu, Y., Xiang, Q., Wang, Y., Cai, L.: Cultural style based music classification of audio signals. In: Proceedings of the ICASSP, Taipei, Taiwan, Apr 2009
251.
Zurück zum Zitat Lo, Y.L., Lin, Y.C.: Content-based music classification. In: Proceedings of the International Conference on Computer Science Information Technology, pp. 112–116 (2010) Lo, Y.L., Lin, Y.C.: Content-based music classification. In: Proceedings of the International Conference on Computer Science Information Technology, pp. 112–116 (2010)
252.
Zurück zum Zitat Loh, Q.J.B., Emmanuel, S.: ELM for the classification of music genres. In: Proceedings of the International Conference on Control, Automation, Robotics and Vision, pp. 1–6 (2006) Loh, Q.J.B., Emmanuel, S.: ELM for the classification of music genres. In: Proceedings of the International Conference on Control, Automation, Robotics and Vision, pp. 1–6 (2006)
253.
Zurück zum Zitat Londei, A., Loreto, V., Belardinelli, M.O.: Musical style and authorship categorization by informative compressors. In: Proceedings of the ESCOM Conference on Hanover, Germany, pp. 200–203, Sept 2003 Londei, A., Loreto, V., Belardinelli, M.O.: Musical style and authorship categorization by informative compressors. In: Proceedings of the ESCOM Conference on Hanover, Germany, pp. 200–203, Sept 2003
254.
Zurück zum Zitat Lopes, M., Gouyon, F., Koerich, A., Oliveira, L.E.S.: Selection of training instances for music genre classification. In: Proceedings of the ICPR, Istanbul, Turkey (2010) Lopes, M., Gouyon, F., Koerich, A., Oliveira, L.E.S.: Selection of training instances for music genre classification. In: Proceedings of the ICPR, Istanbul, Turkey (2010)
255.
Zurück zum Zitat Lukashevich, H., Abeßer, J., Dittmar, C., Großmann, H.: From multi-labeling to multi-domain-labeling: a novel two-dimensional approach to music genre classification. In: Proceedings of the ISMIR (2009) Lukashevich, H., Abeßer, J., Dittmar, C., Großmann, H.: From multi-labeling to multi-domain-labeling: a novel two-dimensional approach to music genre classification. In: Proceedings of the ISMIR (2009)
256.
Zurück zum Zitat Lukashevich, H.: Applying multiple kernel learning to automatic genre classification. In: Gaul, W.A., Geyer-Schulz, A., Schmidt-Thieme, L., Kunze, J. (eds.) Challenges at the Interface of Data Analysis, Computer Science, and Optimization, pp. 393–400. Springer, Berlin (2012) Lukashevich, H.: Applying multiple kernel learning to automatic genre classification. In: Gaul, W.A., Geyer-Schulz, A., Schmidt-Thieme, L., Kunze, J. (eds.) Challenges at the Interface of Data Analysis, Computer Science, and Optimization, pp. 393–400. Springer, Berlin (2012)
257.
Zurück zum Zitat Christanti, M.V., Kurniawan, F., Tony: Automatic music classification for Dangdut and Campursari using Naïve Bayes. In: International Conference on Electrical Engineering and Informatics (2011) Christanti, M.V., Kurniawan, F., Tony: Automatic music classification for Dangdut and Campursari using Naïve Bayes. In: International Conference on Electrical Engineering and Informatics (2011)
258.
Zurück zum Zitat Mace, S.T., Wagoner, C.L., Teachout, D.J., Hodges, D.A.: Genre identification of very brief musical excerpts. Psychol. Music 40(1), 112–128 (2011) Mace, S.T., Wagoner, C.L., Teachout, D.J., Hodges, D.A.: Genre identification of very brief musical excerpts. Psychol. Music 40(1), 112–128 (2011)
259.
Zurück zum Zitat Manaris, B., Romero, J., Machado, P., Krehbiel, D., Hirzel, T., Pharr, W., Davis, R.B.: Zipf’s law, music classification, and aesthetics. Comput. Music J. 29(1), 55–69 (2005) Manaris, B., Romero, J., Machado, P., Krehbiel, D., Hirzel, T., Pharr, W., Davis, R.B.: Zipf’s law, music classification, and aesthetics. Comput. Music J. 29(1), 55–69 (2005)
260.
Zurück zum Zitat Manaris, B., Krehbiel, D., Roos, P., Zalonis, T.: Armonique: experiments in content-based similarity retrieval using power-law melodic and timbre metrics. In: Proceedings of the ISMIR, pp. 343–348 (2008) Manaris, B., Krehbiel, D., Roos, P., Zalonis, T.: Armonique: experiments in content-based similarity retrieval using power-law melodic and timbre metrics. In: Proceedings of the ISMIR, pp. 343–348 (2008)
261.
Zurück zum Zitat Manaris, B., Roos, P., Krehbiel, D., Zalonis, T., Armstrong, J.: Zipf’s law, power laws and music aesthetics. In: Li, T., Ogihara, M., Tzanetakis, G. (eds.) Music Data Mining, pp. 169–216. CRC Press, Boca Raton (2011) Manaris, B., Roos, P., Krehbiel, D., Zalonis, T., Armstrong, J.: Zipf’s law, power laws and music aesthetics. In: Li, T., Ogihara, M., Tzanetakis, G. (eds.) Music Data Mining, pp. 169–216. CRC Press, Boca Raton (2011)
262.
Zurück zum Zitat Mandel, M.I., Poliner, G.E., Ellis, D.P.W.: Support vector machine active learning for music retrieval. Multimed. Syst. 12, 3–13 (2006) Mandel, M.I., Poliner, G.E., Ellis, D.P.W.: Support vector machine active learning for music retrieval. Multimed. Syst. 12, 3–13 (2006)
263.
Zurück zum Zitat Manzagol, P.A., Bertin-Mahieux, T., Eck, D.: On the use of sparse time-relative auditory codes for music. In: Proceedings of the ISMIR, Philadelphia, PA, pp. 603–608, Sept 2008 Manzagol, P.A., Bertin-Mahieux, T., Eck, D.: On the use of sparse time-relative auditory codes for music. In: Proceedings of the ISMIR, Philadelphia, PA, pp. 603–608, Sept 2008
264.
Zurück zum Zitat Markov, K., Matsui, T.: Music genre classification using self-taught learning via sparse coding. In: Proceedings of the ICASSP, pp. 1929–1932, Mar 2012 Markov, K., Matsui, T.: Music genre classification using self-taught learning via sparse coding. In: Proceedings of the ICASSP, pp. 1929–1932, Mar 2012
265.
Zurück zum Zitat Markov, K., Matsui, T.: Nonnegative matrix factorization based self-taught learning with application to music genre classification. In: Proceedings of the IEEE International Workshop on Machine Learning for Signal Processing, pp. 1–5, Sept 2012 Markov, K., Matsui, T.: Nonnegative matrix factorization based self-taught learning with application to music genre classification. In: Proceedings of the IEEE International Workshop on Machine Learning for Signal Processing, pp. 1–5, Sept 2012
266.
Zurück zum Zitat Marques, G., Langlois, T.: A language modeling approach for the classification of music pieces. In: Proceedings of the Data Mining, pp. 193–198 (2009) Marques, G., Langlois, T.: A language modeling approach for the classification of music pieces. In: Proceedings of the Data Mining, pp. 193–198 (2009)
267.
Zurück zum Zitat Marques, G., Lopes, M., Sordo, M., Langlois, T., Gouyon, F.: Additional evidence that common low-level features of individual audio frames are not representative of music genres. In: Proceedings of the SMC, Barcelona, Spain, July 2010 Marques, G., Lopes, M., Sordo, M., Langlois, T., Gouyon, F.: Additional evidence that common low-level features of individual audio frames are not representative of music genres. In: Proceedings of the SMC, Barcelona, Spain, July 2010
268.
Zurück zum Zitat Marques, G., Langlois, T., Gouyon, F., Lopes, M., Sordo, M.: Short-term feature space and music genre classification. J. New Music Res. 40(2), 127–137 (2011) Marques, G., Langlois, T., Gouyon, F., Lopes, M., Sordo, M.: Short-term feature space and music genre classification. J. New Music Res. 40(2), 127–137 (2011)
269.
Zurück zum Zitat Marques, C., Guiherme, I.R., Nakamura, R.Y.M., Papa, J.P.: New trends in musical genre classification using optimum-path forest. In: Proceedings of the ISMIR (2011) Marques, C., Guiherme, I.R., Nakamura, R.Y.M., Papa, J.P.: New trends in musical genre classification using optimum-path forest. In: Proceedings of the ISMIR (2011)
270.
Zurück zum Zitat Martin, K.D., Scheirer, E.D., Vercoe, B.L.: Music content analysis through models of audition. In: Proceedings of the ACM Multimedia Workshop on Content Processing of Music for Multimedia Applications, Sept 1998 Martin, K.D., Scheirer, E.D., Vercoe, B.L.: Music content analysis through models of audition. In: Proceedings of the ACM Multimedia Workshop on Content Processing of Music for Multimedia Applications, Sept 1998
271.
Zurück zum Zitat Matityaho, B., Furst, M.: Neural network based model for classification of music type. In: Proceedings of the Convention of Electrical and Electronics Engineers in Israel, pp. 1–5, Mar 1995 Matityaho, B., Furst, M.: Neural network based model for classification of music type. In: Proceedings of the Convention of Electrical and Electronics Engineers in Israel, pp. 1–5, Mar 1995
272.
Zurück zum Zitat Mayer, R., Neumayer, R., Rauber, A.: Rhyme and style features for musical genre classification by song lyrics. In: Proceedings of the ISMIR (2008) Mayer, R., Neumayer, R., Rauber, A.: Rhyme and style features for musical genre classification by song lyrics. In: Proceedings of the ISMIR (2008)
273.
Zurück zum Zitat Mayer, R., Neumayer, R., Rauber, A.: Combination of audio and lyrics features for genre classification in digital audio collections. In: Proceedings of the ACM Multimedia, pp. 159–168, Oct 2008 Mayer, R., Neumayer, R., Rauber, A.: Combination of audio and lyrics features for genre classification in digital audio collections. In: Proceedings of the ACM Multimedia, pp. 159–168, Oct 2008
274.
Zurück zum Zitat Mayer, R., Rauber, A.: Building ensembles of audio and lyrics features to improve musical genre classification. In: International Conference on Distributed Frameworks for Multimedia Applications (2010) Mayer, R., Rauber, A.: Building ensembles of audio and lyrics features to improve musical genre classification. In: International Conference on Distributed Frameworks for Multimedia Applications (2010)
275.
Zurück zum Zitat Mayer, R., Rauber, A.: Multimodal aspects of music retrieval: audio, song lyrics - and beyond? Stud. Comput. Intell. 274, 333–363 (2010) Mayer, R., Rauber, A.: Multimodal aspects of music retrieval: audio, song lyrics - and beyond? Stud. Comput. Intell. 274, 333–363 (2010)
276.
Zurück zum Zitat Mayer, R., Rauber, A., Ponce de León, P.J., Pérez-Sancho, C., Iñesta, J.M.: Feature selection in a cartesian ensemble of feature subspace classifiers for music categorisation. In: Proceedings of the ACM International Workshop on Machine Learning and Music, pp. 53–56 (2010) Mayer, R., Rauber, A., Ponce de León, P.J., Pérez-Sancho, C., Iñesta, J.M.: Feature selection in a cartesian ensemble of feature subspace classifiers for music categorisation. In: Proceedings of the ACM International Workshop on Machine Learning and Music, pp. 53–56 (2010)
277.
Zurück zum Zitat Mayer, R., Rauber, A.: Music genre classification by ensembles of audio and lyrics features. In: Proceedings of the ISMIR, pp. 675–680 (2011) Mayer, R., Rauber, A.: Music genre classification by ensembles of audio and lyrics features. In: Proceedings of the ISMIR, pp. 675–680 (2011)
278.
Zurück zum Zitat McDermott, J., Hauser, M.D.: Nonhuman primates prefer slow tempos but dislike music overall. Cognition 104(3), 654–668 (2007) McDermott, J., Hauser, M.D.: Nonhuman primates prefer slow tempos but dislike music overall. Cognition 104(3), 654–668 (2007)
279.
Zurück zum Zitat McKay, C., Fujinaga, I.: Automatic genre classification using large high-level musical feature sets. In: Proceedings of the ISMIR (2004) McKay, C., Fujinaga, I.: Automatic genre classification using large high-level musical feature sets. In: Proceedings of the ISMIR (2004)
280.
Zurück zum Zitat McKay, C.: Automatic genre classification of MIDI recordings. Ph.D. thesis, McGill University, Montréal, Canada, June 2004 McKay, C.: Automatic genre classification of MIDI recordings. Ph.D. thesis, McGill University, Montréal, Canada, June 2004
281.
Zurück zum Zitat McKay, C., Fujinaga, I.: Automatic music classification and the importance of instrument identification. In: Proceedings of the Conference on Interdisciplinary Musicology (2005) McKay, C., Fujinaga, I.: Automatic music classification and the importance of instrument identification. In: Proceedings of the Conference on Interdisciplinary Musicology (2005)
282.
Zurück zum Zitat McKay, C., Fujinaga, I.: Music genre classification: is it worth pursuing and how can it be improved? In: Proceedings of the ISMIR, Victoria, Canada, Oct 2006 McKay, C., Fujinaga, I.: Music genre classification: is it worth pursuing and how can it be improved? In: Proceedings of the ISMIR, Victoria, Canada, Oct 2006
283.
Zurück zum Zitat McKay, C., Fujinaga, I.: Combining features extracted from audio, symbolic and cultural sources. In: Proceedings of the ISMIR, pp. 597–602 (2008) McKay, C., Fujinaga, I.: Combining features extracted from audio, symbolic and cultural sources. In: Proceedings of the ISMIR, pp. 597–602 (2008)
284.
Zurück zum Zitat McKay, C.: Automatic music classification with jMIR. Ph.D. thesis, McGill University, Montréal, Canada, Jan 2010 McKay, C.: Automatic music classification with jMIR. Ph.D. thesis, McGill University, Montréal, Canada, Jan 2010
285.
Zurück zum Zitat McKay, C., Fujinaga, I.: Improving automatic music classification performance by extracting features from different types of data. In: Multimedia Information Retrieval, pp. 257–266 (2010) McKay, C., Fujinaga, I.: Improving automatic music classification performance by extracting features from different types of data. In: Multimedia Information Retrieval, pp. 257–266 (2010)
286.
Zurück zum Zitat McKay, C., Burgoyne, J.A., Hockman, J., Smith, J.B.L., Vigliensoni, G., Fujinaga, I.: Evaluating the genre classification performance of lyrical features relative to audio, symbolic and cultural features. In: Proceedings of the ISMIR, pp. 213–218 (2010) McKay, C., Burgoyne, J.A., Hockman, J., Smith, J.B.L., Vigliensoni, G., Fujinaga, I.: Evaluating the genre classification performance of lyrical features relative to audio, symbolic and cultural features. In: Proceedings of the ISMIR, pp. 213–218 (2010)
287.
Zurück zum Zitat McKinney, M.F., Breebaart, J.: Features for audio and music classification. In: Proceedings of the ISMIR, Baltimore, MD, Oct 2003 McKinney, M.F., Breebaart, J.: Features for audio and music classification. In: Proceedings of the ISMIR, Baltimore, MD, Oct 2003
288.
Zurück zum Zitat Mendes, R.S., Ribeiro, H.V., Freire, F.C.M., Tateishi, A.A., Lenzi, E.K.: Universal patterns in sound amplitudes of songs and music genres. Phys. Rev. E 83, 017101 (2011) Mendes, R.S., Ribeiro, H.V., Freire, F.C.M., Tateishi, A.A., Lenzi, E.K.: Universal patterns in sound amplitudes of songs and music genres. Phys. Rev. E 83, 017101 (2011)
289.
Zurück zum Zitat Meng, A., Ahrendt, P., Larsen, J.: Improving music genre classification by short-time feature integration. In: Proceedings of the ICASSP, Philadelphia, PA, pp. 497–500, Mar 2005 Meng, A., Ahrendt, P., Larsen, J.: Improving music genre classification by short-time feature integration. In: Proceedings of the ICASSP, Philadelphia, PA, pp. 497–500, Mar 2005
290.
Zurück zum Zitat Meng, A.: Temporal feature integration for music organization. Ph.D. thesis, Technical University of Denmark (2006) Meng, A.: Temporal feature integration for music organization. Ph.D. thesis, Technical University of Denmark (2006)
291.
Zurück zum Zitat Meng, A., Shawe-Taylor, J.: An investigation of feature models for music genre classification using the support vector classifier. In: Proceedings of the ISMIR (2008) Meng, A., Shawe-Taylor, J.: An investigation of feature models for music genre classification using the support vector classifier. In: Proceedings of the ISMIR (2008)
292.
Zurück zum Zitat Mierswa, I., Morik, K.: Automatic feature extraction for classifying audio data. Mach. Learn. 58(2–3), 127–149 (2005)MATH Mierswa, I., Morik, K.: Automatic feature extraction for classifying audio data. Mach. Learn. 58(2–3), 127–149 (2005)MATH
300.
Zurück zum Zitat Mitra, V., Wang, C.J.: Content based audio classification: a neural network approach. Soft Comput. - A Fusion Found. Methodol. Appl. 12, 639–646 (2008) Mitra, V., Wang, C.J.: Content based audio classification: a neural network approach. Soft Comput. - A Fusion Found. Methodol. Appl. 12, 639–646 (2008)
301.
Zurück zum Zitat Mitri, G., Uitdenbogerd, A.L., Ciesielski, V.: Automatic music classification problems. In: Proceedings of the Autralasian Computer Science Conference (2004) Mitri, G., Uitdenbogerd, A.L., Ciesielski, V.: Automatic music classification problems. In: Proceedings of the Autralasian Computer Science Conference (2004)
302.
Zurück zum Zitat Moerchen, F., Ultsch, A., Nöcker, M., Stamm, C.: Databionic visualization of music collections according to perceptual distance. In: Proceedings of the ISMIR, London, UK, pp. 396–403, Sept 2005 Moerchen, F., Ultsch, A., Nöcker, M., Stamm, C.: Databionic visualization of music collections according to perceptual distance. In: Proceedings of the ISMIR, London, UK, pp. 396–403, Sept 2005
303.
Zurück zum Zitat Moerchen, F., Mierswa, I., Ultsch, A.: Understandable models of music collections based on exhaustive feature generation with temporal statistics. In: International Conference on Knowledge Discover and Data Mining (2006) Moerchen, F., Mierswa, I., Ultsch, A.: Understandable models of music collections based on exhaustive feature generation with temporal statistics. In: International Conference on Knowledge Discover and Data Mining (2006)
304.
Zurück zum Zitat Mostafa, M.M., Billor, N.: Recognition of western style musical genres using machine learning techniques. Expert Syst. Appl. 36(8), 11378–11389 (2009) Mostafa, M.M., Billor, N.: Recognition of western style musical genres using machine learning techniques. Expert Syst. Appl. 36(8), 11378–11389 (2009)
305.
Zurück zum Zitat Nagathil, A., Gerkmann, T., Martin, R.: Musical genre classification based on highly-resolved cepstral modulation spectrum. In: Proceedings of the EUSIPCO, Aalborg, Denmark, pp. 462–466, Aug 2010 Nagathil, A., Gerkmann, T., Martin, R.: Musical genre classification based on highly-resolved cepstral modulation spectrum. In: Proceedings of the EUSIPCO, Aalborg, Denmark, pp. 462–466, Aug 2010
306.
Zurück zum Zitat Nagathil, A., Göttel, P., Martin, R.: Hierarchical audio classification using cepstral modulation ratio regressions based on Legendre polynomials. In: Proceedings of the ICASSP, pp. 2216–2219, July 2011 Nagathil, A., Göttel, P., Martin, R.: Hierarchical audio classification using cepstral modulation ratio regressions based on Legendre polynomials. In: Proceedings of the ICASSP, pp. 2216–2219, July 2011
307.
Zurück zum Zitat Nayak, S., Bhutani, A.: Music genre classification using GA-induced minimal feature-set. In: Proceedings of the National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics (2011) Nayak, S., Bhutani, A.: Music genre classification using GA-induced minimal feature-set. In: Proceedings of the National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics (2011)
308.
Zurück zum Zitat Neubarth, K., Goienetxea, I., Johnson, C., Conklin, D.: Association mining of folk music genres and toponyms. In: Proceedings of the ISMIR (2012) Neubarth, K., Goienetxea, I., Johnson, C., Conklin, D.: Association mining of folk music genres and toponyms. In: Proceedings of the ISMIR (2012)
309.
Zurück zum Zitat Neumayer, R., Rauber, A.: Integration of text and audio features for genre classification in music information retrieval. In: Amati, G., Carpineto, C., Romano, G. (eds.) ECiR 2007. LNCS, vol. 4425, pp. 724–727. Springer, Heidelberg (2007) Neumayer, R., Rauber, A.: Integration of text and audio features for genre classification in music information retrieval. In: Amati, G., Carpineto, C., Romano, G. (eds.) ECiR 2007. LNCS, vol. 4425, pp. 724–727. Springer, Heidelberg (2007)
310.
Zurück zum Zitat Ni, Y., McVicar, M., Santos, R., Bie, T.D.: Using hyper-genre training to explore genre information for automatic chord estimation. In: Proceedings of the ISMIR (2012) Ni, Y., McVicar, M., Santos, R., Bie, T.D.: Using hyper-genre training to explore genre information for automatic chord estimation. In: Proceedings of the ISMIR (2012)
311.
Zurück zum Zitat Nie, F., Xiang, S., Song, Y., Zhang, C.: Extracting the optimal dimensionality for local tensor discriminant analysis. Pattern Recogn. 42(1), 105–114 (2009)MATH Nie, F., Xiang, S., Song, Y., Zhang, C.: Extracting the optimal dimensionality for local tensor discriminant analysis. Pattern Recogn. 42(1), 105–114 (2009)MATH
312.
Zurück zum Zitat Nopthaisong, C., Hasan, M.M.: Automatic music classification and retrieval: experiments with Thai music collection. In: Proceedings of the International Conference on Information and Communication Technology, pp. 76–81, Mar 2007 Nopthaisong, C., Hasan, M.M.: Automatic music classification and retrieval: experiments with Thai music collection. In: Proceedings of the International Conference on Information and Communication Technology, pp. 76–81, Mar 2007
313.
Zurück zum Zitat Norowi, N.M., Doraisamy, S., Wirza, R.: Factors affecting automatic genre classification: an investigation incorporating non-western musical forms. In: Proceedings of the ISMIR (2005) Norowi, N.M., Doraisamy, S., Wirza, R.: Factors affecting automatic genre classification: an investigation incorporating non-western musical forms. In: Proceedings of the ISMIR (2005)
314.
Zurück zum Zitat Novello, A., McKinney, M.F., Kohlrausch, A.: Perceptual evaluation of music similarity. In: Proceedings of the ISMIR, pp. 246–249 (2006) Novello, A., McKinney, M.F., Kohlrausch, A.: Perceptual evaluation of music similarity. In: Proceedings of the ISMIR, pp. 246–249 (2006)
315.
Zurück zum Zitat Orio, N.: Music retrieval: a tutorial and review. Found. Trends Inf. Retr. 1(1), 1–90 (2006)MATH Orio, N.: Music retrieval: a tutorial and review. Found. Trends Inf. Retr. 1(1), 1–90 (2006)MATH
316.
Zurück zum Zitat Orio, N., Rizo, D., Miotto, R., Schedl, M., Montecchio, N., Lartillot, O.: MusiClef: a benchmark activity in multimodal music information retrieval. In: Proceedings of the ISMIR, pp. 603–608 (2011) Orio, N., Rizo, D., Miotto, R., Schedl, M., Montecchio, N., Lartillot, O.: MusiClef: a benchmark activity in multimodal music information retrieval. In: Proceedings of the ISMIR, pp. 603–608 (2011)
317.
Zurück zum Zitat Otsuka, Y., Yanagi, J., Watanabe, S.: Discriminative and reinforcing stimulus properties of music for rats. Behav. Process. 80(2), 121–127 (2009) Otsuka, Y., Yanagi, J., Watanabe, S.: Discriminative and reinforcing stimulus properties of music for rats. Behav. Process. 80(2), 121–127 (2009)
318.
Zurück zum Zitat Pampalk, E., Dixon, S., Widmer, G.: On the evaluation of perceptual similarity measures for music. In: Proceedings of the DAFx, London, UK, pp. 7–12, Sept 2003 Pampalk, E., Dixon, S., Widmer, G.: On the evaluation of perceptual similarity measures for music. In: Proceedings of the DAFx, London, UK, pp. 7–12, Sept 2003
319.
Zurück zum Zitat Pampalk, E., Flexer, A., Widmer, G.: Improvements of audio-based music similarity and genre classification. In: Proceedings of the ISMIR, London, UK, pp. 628–233, Sept 2005 Pampalk, E., Flexer, A., Widmer, G.: Improvements of audio-based music similarity and genre classification. In: Proceedings of the ISMIR, London, UK, pp. 628–233, Sept 2005
320.
Zurück zum Zitat Pampalk, E.: Computational models of music similarity and their application in music information retrieval. Ph.D. thesis, Vienna University of Technology, Vienna, Austria, Mar 2006 Pampalk, E.: Computational models of music similarity and their application in music information retrieval. Ph.D. thesis, Vienna University of Technology, Vienna, Austria, Mar 2006
321.
Zurück zum Zitat Panagakis, Y., Benetos, E., Kotropoulos, C.: Music genre classification: a multilinear approach. In: Proceedings of the ISMIR, Philadelphia, PA, pp. 583–588, Sept 2008 Panagakis, Y., Benetos, E., Kotropoulos, C.: Music genre classification: a multilinear approach. In: Proceedings of the ISMIR, Philadelphia, PA, pp. 583–588, Sept 2008
322.
Zurück zum Zitat Panagakis, Y., Kotropoulos, C., Arce, G.R.: Music genre classification via sparse representations of auditory temporal modulations. In: Proceedings of the EUSIPCO, Glasgow, Scotland, Aug 2009 Panagakis, Y., Kotropoulos, C., Arce, G.R.: Music genre classification via sparse representations of auditory temporal modulations. In: Proceedings of the EUSIPCO, Glasgow, Scotland, Aug 2009
323.
Zurück zum Zitat Panagakis, Y., Kotropoulos, C., Arce, G.R.: Music genre classification using locality preserving non-negative tensor factorization and sparse representations. In: Proceedings of the ISMIR, Kobe, Japan, pp. 249–254, Oct 2009 Panagakis, Y., Kotropoulos, C., Arce, G.R.: Music genre classification using locality preserving non-negative tensor factorization and sparse representations. In: Proceedings of the ISMIR, Kobe, Japan, pp. 249–254, Oct 2009
324.
Zurück zum Zitat Panagakis, Y., Kotropoulos, C., Arce, G.R.: Non-negative multilinear principal component analysis of auditory temporal modulations for music genre classification. IEEE Trans. Acoust. Speech Lang. Process. 18(3), 576–588 (2010) Panagakis, Y., Kotropoulos, C., Arce, G.R.: Non-negative multilinear principal component analysis of auditory temporal modulations for music genre classification. IEEE Trans. Acoust. Speech Lang. Process. 18(3), 576–588 (2010)
325.
Zurück zum Zitat Panagakis, Y., Kotropoulos, C., Arce, G.R.: Sparse multi-label linear embedding nonnegative tensor factorization for automatic music tagging. In: Proceedings of the EUSIPCO, pp. 492–496, Aug 2010 Panagakis, Y., Kotropoulos, C., Arce, G.R.: Sparse multi-label linear embedding nonnegative tensor factorization for automatic music tagging. In: Proceedings of the EUSIPCO, pp. 492–496, Aug 2010
326.
Zurück zum Zitat Panagakis, Y., Kotropoulos, C.: Music genre classification via topology preserving non-negative tensor factorization and sparse representations. In: Proceedings of the ICASSP, pp. 249–252, Mar 2010 Panagakis, Y., Kotropoulos, C.: Music genre classification via topology preserving non-negative tensor factorization and sparse representations. In: Proceedings of the ICASSP, pp. 249–252, Mar 2010
327.
Zurück zum Zitat Paradzinets, A., Harb, H., Chen, L.: Multiexpert system for automatic music genre classification. Technical report, Ecole Centrale de Lyon, Lyon, France, June 2009 Paradzinets, A., Harb, H., Chen, L.: Multiexpert system for automatic music genre classification. Technical report, Ecole Centrale de Lyon, Lyon, France, June 2009
328.
Zurück zum Zitat Park, D.C.: Classification of audio signals using fuzzy c-means with divergence-based kernel. Pattern Recon. Lett. 30(9), 794–798 (2009) Park, D.C.: Classification of audio signals using fuzzy c-means with divergence-based kernel. Pattern Recon. Lett. 30(9), 794–798 (2009)
329.
Zurück zum Zitat Park, D.C.: Partitioned feature-based classifier model. In: Proceedings of the IEEE International Symposium on Signal Processing and Information Technology, pp. 412–417 (2009) Park, D.C.: Partitioned feature-based classifier model. In: Proceedings of the IEEE International Symposium on Signal Processing and Information Technology, pp. 412–417 (2009)
330.
Zurück zum Zitat Park, D.C.: Partitioned feature-based classifier model with expertise table. In: Proceedings of the IEEE International Conference on Bio-inspired Computing (2010) Park, D.C.: Partitioned feature-based classifier model with expertise table. In: Proceedings of the IEEE International Conference on Bio-inspired Computing (2010)
331.
Zurück zum Zitat Park, S., Park, J., Sim, K.: Optimization system of musical expression for the music genre classification. In: Proceedings of the International Conference on Control, Automation, and Systems, pp. 1644–1648, Oct 2011 Park, S., Park, J., Sim, K.: Optimization system of musical expression for the music genre classification. In: Proceedings of the International Conference on Control, Automation, and Systems, pp. 1644–1648, Oct 2011
332.
Zurück zum Zitat Peeters, G.: A generic system for audio indexing: application to speech/music segmentation and music genre recognition. In: Proceedings of the DAFx, Bordeaux, France, Sept 2007 Peeters, G.: A generic system for audio indexing: application to speech/music segmentation and music genre recognition. In: Proceedings of the DAFx, Bordeaux, France, Sept 2007
333.
Zurück zum Zitat Peeters, G.: Spectral and temporal periodicity representations of rhythm for the automatic classification of music audio signal. IEEE Trans. Audio Speech Lang. Process. 19(5), 1242–1252 (2011) Peeters, G.: Spectral and temporal periodicity representations of rhythm for the automatic classification of music audio signal. IEEE Trans. Audio Speech Lang. Process. 19(5), 1242–1252 (2011)
334.
Zurück zum Zitat Peng, W., Li, T., Ogihara, M.: Music clustering with constraints. In: Proceedings of the ISMIR, pp. 27–32 (2007) Peng, W., Li, T., Ogihara, M.: Music clustering with constraints. In: Proceedings of the ISMIR, pp. 27–32 (2007)
335.
Zurück zum Zitat Pérez-Sancho, C., Iñesta, J.M., Calera-Rubio, J.: A text categorization approach for music style recognition. In: Marques, J.S., Pérez de la Blanca, N., Pina, P. (eds.) IbPRIA 2005. LNCS, vol. 3523, pp. 649–657. Springer, Heidelberg (2005) Pérez-Sancho, C., Iñesta, J.M., Calera-Rubio, J.: A text categorization approach for music style recognition. In: Marques, J.S., Pérez de la Blanca, N., Pina, P. (eds.) IbPRIA 2005. LNCS, vol. 3523, pp. 649–657. Springer, Heidelberg (2005)
336.
Zurück zum Zitat Iñesta, T.P.J.M., Rizo, D.: metamidi: a tool for automatic metadata extraction from MIDI files. In: Proceedings of the Workshop on Exploring Musical Information Spaces, pp. 36–40, Oct 2009 Iñesta, T.P.J.M., Rizo, D.: metamidi: a tool for automatic metadata extraction from MIDI files. In: Proceedings of the Workshop on Exploring Musical Information Spaces, pp. 36–40, Oct 2009
337.
Zurück zum Zitat Pérez-García, T., Pérez-Sancho, C., Iñesta, J.: Harmonic and instrumental information fusion for musical genre classification. In: Proceedings of the ACM International Workshop on Machine Learning and Music, pp. 49–52 (2010) Pérez-García, T., Pérez-Sancho, C., Iñesta, J.: Harmonic and instrumental information fusion for musical genre classification. In: Proceedings of the ACM International Workshop on Machine Learning and Music, pp. 49–52 (2010)
338.
Zurück zum Zitat Pérez-Sancho, C., Iñesta, J.M., Calera-Rubio, J.: Style recognition through statistical event models. J. New Music Res. 34(4), 331–340 (2005) Pérez-Sancho, C., Iñesta, J.M., Calera-Rubio, J.: Style recognition through statistical event models. J. New Music Res. 34(4), 331–340 (2005)
339.
Zurück zum Zitat Pérez-Sancho, C., Rizo, D., Iñesta, J.: Stochastic text models for music categorization. In: da Vitoria Lobo, N., et al. (eds.) SSPR & SPR 2008. LNCS, vol. 5342, pp. 55–64. Springer, Heidelberg (2008) Pérez-Sancho, C., Rizo, D., Iñesta, J.: Stochastic text models for music categorization. In: da Vitoria Lobo, N., et al. (eds.) SSPR & SPR 2008. LNCS, vol. 5342, pp. 55–64. Springer, Heidelberg (2008)
340.
Zurück zum Zitat Pérez-Sancho, C., Rizo, D., Iñesta, J.M.: Genre classification using chords and stochastic language models. Connect. Sci. 21, 145–159 (2009) Pérez-Sancho, C., Rizo, D., Iñesta, J.M.: Genre classification using chords and stochastic language models. Connect. Sci. 21, 145–159 (2009)
341.
Zurück zum Zitat Pérez-Sancho, C.: Stochastic language models for music information retrieval. Ph.D. thesis, Universidad de Alicante, Spain, June 2009 Pérez-Sancho, C.: Stochastic language models for music information retrieval. Ph.D. thesis, Universidad de Alicante, Spain, June 2009
342.
Zurück zum Zitat Pohle, T.: Extraction of audio descriptors and their evaluation in music classification tasks. Ph.D. thesis, Technischen Universität Kaiserslautern, Jan 2005 Pohle, T.: Extraction of audio descriptors and their evaluation in music classification tasks. Ph.D. thesis, Technischen Universität Kaiserslautern, Jan 2005
343.
Zurück zum Zitat Pohle, T., Knees, P., Schedl, M., Widmer, G.: Independent component analysis for music similarity computation. In: Proceedings of ISMIR, pp. 228–233 (2006) Pohle, T., Knees, P., Schedl, M., Widmer, G.: Independent component analysis for music similarity computation. In: Proceedings of ISMIR, pp. 228–233 (2006)
344.
Zurück zum Zitat Pohle, T., Pampalk, E., Widmer, G.: Evaluation of frequently used audio features for classification of music into perceptual categories. In: International Workshop on Content-Based Multimedia Indexing (2008) Pohle, T., Pampalk, E., Widmer, G.: Evaluation of frequently used audio features for classification of music into perceptual categories. In: International Workshop on Content-Based Multimedia Indexing (2008)
345.
Zurück zum Zitat Pohle, T., Schnitzer, D., Schedl, M., Knees, P., Widmer, G.: On rhythm and general music similarity. In: Proceedings of the ISMIR (2009) Pohle, T., Schnitzer, D., Schedl, M., Knees, P., Widmer, G.: On rhythm and general music similarity. In: Proceedings of the ISMIR (2009)
346.
Zurück zum Zitat Pollastri, E., Simoncelli, G.: Classification of melodies by composer with hidden Markov models. In: Proceedings of the WEDELMUSIC, pp. 88–95, Nov 2001 Pollastri, E., Simoncelli, G.: Classification of melodies by composer with hidden Markov models. In: Proceedings of the WEDELMUSIC, pp. 88–95, Nov 2001
347.
Zurück zum Zitat Porter, D., Neuringer, A.: Music discriminations by pigeons. Exp. Psychol.: Animal Behav. Process. 10(2), 138–148 (1984) Porter, D., Neuringer, A.: Music discriminations by pigeons. Exp. Psychol.: Animal Behav. Process. 10(2), 138–148 (1984)
348.
Zurück zum Zitat Pye, D.: Content-based methods for the management of digital music. In: Proceedings of the ICASSP (2000) Pye, D.: Content-based methods for the management of digital music. In: Proceedings of the ICASSP (2000)
349.
Zurück zum Zitat Rafailidis, D., Nanopoulos, A., Manolopoulos, Y.: Nonlinear dimensionality reduction for efficient and effective audio similarity searching. Multimed. Tools Appl. 42, 273–293 (2009) Rafailidis, D., Nanopoulos, A., Manolopoulos, Y.: Nonlinear dimensionality reduction for efficient and effective audio similarity searching. Multimed. Tools Appl. 42, 273–293 (2009)
350.
Zurück zum Zitat Rauber, A., Frühwirth, M.: Automatically analyzing and organizing music archives. In: Constantopoulos, P., Sølvberg, I.T. (eds.) ECDL 2001. LNCS, vol. 2163, p. 402. Springer, Heidelberg (2001) Rauber, A., Frühwirth, M.: Automatically analyzing and organizing music archives. In: Constantopoulos, P., Sølvberg, I.T. (eds.) ECDL 2001. LNCS, vol. 2163, p. 402. Springer, Heidelberg (2001)
351.
Zurück zum Zitat Rauber, A., Pampalk, E., Merkl, D.: Using psycho-acoustic models and self-organizing maps to create a hierarchical structuring of music by musical styles. In: Proceedings of the ISMIR, pp. 71–80, Oct 2002 Rauber, A., Pampalk, E., Merkl, D.: Using psycho-acoustic models and self-organizing maps to create a hierarchical structuring of music by musical styles. In: Proceedings of the ISMIR, pp. 71–80, Oct 2002
352.
Zurück zum Zitat Ravelli, E., Richard, G., Daudet, L.: Audio signal representations for indexing in the transform domain. IEEE Trans. Audio Speech Lang. Process. 18(3), 434–446 (2010) Ravelli, E., Richard, G., Daudet, L.: Audio signal representations for indexing in the transform domain. IEEE Trans. Audio Speech Lang. Process. 18(3), 434–446 (2010)
353.
Zurück zum Zitat Reed, J., Lee, C.H.: A study on music genre classification based on universal acoustic models. In: Proceedings of the ISMIR (2006) Reed, J., Lee, C.H.: A study on music genre classification based on universal acoustic models. In: Proceedings of the ISMIR (2006)
354.
Zurück zum Zitat Reed, J., Lee, C.H.: A study on attribute-based taxonomy for music information retrieval. In: Proceedings of the ISMIR, pp. 485–490 (2007) Reed, J., Lee, C.H.: A study on attribute-based taxonomy for music information retrieval. In: Proceedings of the ISMIR, pp. 485–490 (2007)
355.
Zurück zum Zitat Rin, J.M., Chen, Z.S., Jang, J.S.R.: On the use of sequential patterns mining as temporal features for music genre classification. In: Proceedings of the ICASSP (2010) Rin, J.M., Chen, Z.S., Jang, J.S.R.: On the use of sequential patterns mining as temporal features for music genre classification. In: Proceedings of the ICASSP (2010)
356.
Zurück zum Zitat Ren, J.M., Jang, J.S.R.: Time-constrained sequential pattern discovery for music genre classification. In: Proceedings of the ICASSP, pp. 173–176 (2011) Ren, J.M., Jang, J.S.R.: Time-constrained sequential pattern discovery for music genre classification. In: Proceedings of the ICASSP, pp. 173–176 (2011)
357.
Zurück zum Zitat Ren, J.M., Jang, J.S.R.: Discovering time-constrained sequential patterns for music genre classification. IEEE Trans. Audio Speech Lang. Process. 20(4), 1134–1144 (2012) Ren, J.M., Jang, J.S.R.: Discovering time-constrained sequential patterns for music genre classification. IEEE Trans. Audio Speech Lang. Process. 20(4), 1134–1144 (2012)
358.
Zurück zum Zitat Ribeiro, H., Zunino, L., Mendes, R., Lenzi, E.: Complexity-entropy causality plane: a useful approach for distinguishing songs. Phys. A: Stat. Mech. Its Appl. 391(7), 2421–2428 (2012) Ribeiro, H., Zunino, L., Mendes, R., Lenzi, E.: Complexity-entropy causality plane: a useful approach for distinguishing songs. Phys. A: Stat. Mech. Its Appl. 391(7), 2421–2428 (2012)
359.
Zurück zum Zitat Rizzi, A., Buccino, N.M., Panella, M., Uncini, A.: Genre classification of compressed audio data. In: Proceedings of the International Workshop on Multimedia Signal Processing (2008) Rizzi, A., Buccino, N.M., Panella, M., Uncini, A.: Genre classification of compressed audio data. In: Proceedings of the International Workshop on Multimedia Signal Processing (2008)
360.
Zurück zum Zitat Ro, W., Kwon, Y.: 1/f noise analysis of songs in various genre of music. Chaos Soliton. Fract. 42(4), 2305–2311 (2009) Ro, W., Kwon, Y.: 1/f noise analysis of songs in various genre of music. Chaos Soliton. Fract. 42(4), 2305–2311 (2009)
361.
Zurück zum Zitat Rocha, B.: Genre classification based on predominant melodic pitch contours. Master’s thesis, Universitat Pompeu Fabra, Barcelona, Spain, Sept 2011 Rocha, B.: Genre classification based on predominant melodic pitch contours. Master’s thesis, Universitat Pompeu Fabra, Barcelona, Spain, Sept 2011
362.
Zurück zum Zitat Rump, H., Miyabe, S., Tsunoo, E., Ono, N., Sagayama, S.: Autoregressive MFCC models for genre classification improved by harmonic-percussion separation. In: Proceedings of the ISMIR, pp. 87–92 (2010) Rump, H., Miyabe, S., Tsunoo, E., Ono, N., Sagayama, S.: Autoregressive MFCC models for genre classification improved by harmonic-percussion separation. In: Proceedings of the ISMIR, pp. 87–92 (2010)
363.
Zurück zum Zitat Ruppin, A., Yeshurun, H.: Midi music genre classification by invariant features. In: Proceedings of the ISMIR, pp. 397–399 (2006) Ruppin, A., Yeshurun, H.: Midi music genre classification by invariant features. In: Proceedings of the ISMIR, pp. 397–399 (2006)
364.
Zurück zum Zitat Salamon, J., Rocha, B., Gomez, E.: Musical genre classification using melody features extracted from polyphonic music signals. In: Proceedings of the ICASSP, Kyoto, Japan, Mar 2012 Salamon, J., Rocha, B., Gomez, E.: Musical genre classification using melody features extracted from polyphonic music signals. In: Proceedings of the ICASSP, Kyoto, Japan, Mar 2012
365.
Zurück zum Zitat Sanden, C., Befus, C., Zhang, J.Z.: Clustering-based genre prediction on music data. In: Proceedings of the International C* Conference on Computer Science and Software Engineering, pp. 117–119 (2008) Sanden, C., Befus, C., Zhang, J.Z.: Clustering-based genre prediction on music data. In: Proceedings of the International C* Conference on Computer Science and Software Engineering, pp. 117–119 (2008)
366.
Zurück zum Zitat Sanden, C., Befus, C.R., Zhang, J.: Perception based multi-label genre classification on music data. In: Proceedings of the ICMC, pp. 9–15 (2010) Sanden, C., Befus, C.R., Zhang, J.: Perception based multi-label genre classification on music data. In: Proceedings of the ICMC, pp. 9–15 (2010)
367.
Zurück zum Zitat Sanden, C.: An empirical evaluation of computational and perceptual multi-label genre classification on music. Master’s thesis, University of Lethbridge (2010) Sanden, C.: An empirical evaluation of computational and perceptual multi-label genre classification on music. Master’s thesis, University of Lethbridge (2010)
368.
Zurück zum Zitat Sanden, C., Zhang, J.Z.: Enhancing multi-label music genre classification through ensemble techniques. In: Proceedings of the International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 705–714 (2011) Sanden, C., Zhang, J.Z.: Enhancing multi-label music genre classification through ensemble techniques. In: Proceedings of the International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 705–714 (2011)
369.
Zurück zum Zitat Sanden, C., Zhang, J.Z.: Algorithmic multi-genre classification of music: an empirical study. In: Proceedings of the ICMC (2011) Sanden, C., Zhang, J.Z.: Algorithmic multi-genre classification of music: an empirical study. In: Proceedings of the ICMC (2011)
370.
Zurück zum Zitat Sanden, C., Befus, C.R., Zhang, J.Z.: A perceptual study on music segmentation and genre classification. J. New Music Res. 41(3), 277–293 (2012) Sanden, C., Befus, C.R., Zhang, J.Z.: A perceptual study on music segmentation and genre classification. J. New Music Res. 41(3), 277–293 (2012)
371.
Zurück zum Zitat de los Santos, C.A.: Nonlinear audio recurrence analysis with application to music genre classification. Master’s thesis, Universitat Pompeu Fabra, Barcelona, Spain (2010) de los Santos, C.A.: Nonlinear audio recurrence analysis with application to music genre classification. Master’s thesis, Universitat Pompeu Fabra, Barcelona, Spain (2010)
372.
Zurück zum Zitat Scaringella, N., Zoia, G.: On the modeling of time information for automatic genre recognition systems in audio signals. In: Proceedings of the ISMIR, pp. 666–671 (2005) Scaringella, N., Zoia, G.: On the modeling of time information for automatic genre recognition systems in audio signals. In: Proceedings of the ISMIR, pp. 666–671 (2005)
373.
Zurück zum Zitat Scaringella, N., Zoia, G., Mlynek, D.: Automatic genre classification of music content: a survey. IEEE Signal Process. Mag. 23(2), 133–141 (2006) Scaringella, N., Zoia, G., Mlynek, D.: Automatic genre classification of music content: a survey. IEEE Signal Process. Mag. 23(2), 133–141 (2006)
374.
Zurück zum Zitat Schedl, M., Pohle, T., Knees, P., Widmer, G.: Assigning and visualizing music genres by web-based co-occurrence analysis. In: Proceedings of the ISMIR (2006) Schedl, M., Pohle, T., Knees, P., Widmer, G.: Assigning and visualizing music genres by web-based co-occurrence analysis. In: Proceedings of the ISMIR (2006)
375.
Zurück zum Zitat Schierz, A., Budka, M.: High-performance music information retrieval system for song genre classification. In: Kryszkiewicz, M., Rybinski, H., Skowron, A., Raś, Z.W. (eds.) ISMIS 2011. LNCS (LNAI), vol. 6804, pp. 725–733. Springer, Heidelberg (2011) Schierz, A., Budka, M.: High-performance music information retrieval system for song genre classification. In: Kryszkiewicz, M., Rybinski, H., Skowron, A., Raś, Z.W. (eds.) ISMIS 2011. LNCS (LNAI), vol. 6804, pp. 725–733. Springer, Heidelberg (2011)
376.
Zurück zum Zitat Schindler, A., Mayer, R., Rauber, A.: Facilitating comprehensive benchmarking experiments on the million song dataset. In: Proceedings of the ISMIR, Oct 2012 Schindler, A., Mayer, R., Rauber, A.: Facilitating comprehensive benchmarking experiments on the million song dataset. In: Proceedings of the ISMIR, Oct 2012
377.
Zurück zum Zitat Schindler, A., Rauber, A.: Capturing the temporal domain in echonest features for improved classification effectiveness. In: Proceedings of the Adaptive Multimedia Retrieval, Oct 2012 Schindler, A., Rauber, A.: Capturing the temporal domain in echonest features for improved classification effectiveness. In: Proceedings of the Adaptive Multimedia Retrieval, Oct 2012
378.
Zurück zum Zitat Schlüter, J., Osendorfer, C.: Music similarity estimation with the mean-covariance restricted Boltzmann machine. In: Proceedings of the ICMLA (2011) Schlüter, J., Osendorfer, C.: Music similarity estimation with the mean-covariance restricted Boltzmann machine. In: Proceedings of the ICMLA (2011)
379.
Zurück zum Zitat Seo, J., Lee, S.: Higher-order moments for musical genre classification. Signal Process. 91(8), 2154–2157 (2011)MATH Seo, J., Lee, S.: Higher-order moments for musical genre classification. Signal Process. 91(8), 2154–2157 (2011)MATH
380.
Zurück zum Zitat Serra, J., de los Santos, C.A., Andrzejak, R.G.: Nonlinear audio recurrence analysis with application to genre classification. In: Proceedings of the ICASSP (2011) Serra, J., de los Santos, C.A., Andrzejak, R.G.: Nonlinear audio recurrence analysis with application to genre classification. In: Proceedings of the ICASSP (2011)
381.
Zurück zum Zitat Seyerlehner, K.: Content-based music recommender systems: beyond simple frame-level audio similarity. Ph.D. thesis, Johannes Kepler University, Linz, Austria, Dec 2010 Seyerlehner, K.: Content-based music recommender systems: beyond simple frame-level audio similarity. Ph.D. thesis, Johannes Kepler University, Linz, Austria, Dec 2010
382.
Zurück zum Zitat Seyerlehner, K., Widmer, G., Pohle, T.: Fusing block-level features for music similarity estimation. In: Proceedings of the DAFx (2010) Seyerlehner, K., Widmer, G., Pohle, T.: Fusing block-level features for music similarity estimation. In: Proceedings of the DAFx (2010)
383.
Zurück zum Zitat Seyerlehner, K., Widmer, G., Knees, P.: A comparison of human, automatic and collaborative music genre classification and user centric evaluation of genre classification systems. In: Detyniecki, M., Knees, P., Nürnberger, A., Schedl, M., Stober, S. (eds.) AMR 2010. LNCS, vol. 6817, pp. 118–131. Springer, Heidelberg (2012) Seyerlehner, K., Widmer, G., Knees, P.: A comparison of human, automatic and collaborative music genre classification and user centric evaluation of genre classification systems. In: Detyniecki, M., Knees, P., Nürnberger, A., Schedl, M., Stober, S. (eds.) AMR 2010. LNCS, vol. 6817, pp. 118–131. Springer, Heidelberg (2012)
384.
Zurück zum Zitat Seyerlehner, K., Schedl, M., Sonnleitner, R., Hauger, D., Ionescu, B.: From improved auto-taggers to improved music similarity measures. In: Proceedings of the Adaptive Multimedia Retrieval, Copenhagen, Denmark, Oct 2012 Seyerlehner, K., Schedl, M., Sonnleitner, R., Hauger, D., Ionescu, B.: From improved auto-taggers to improved music similarity measures. In: Proceedings of the Adaptive Multimedia Retrieval, Copenhagen, Denmark, Oct 2012
385.
Zurück zum Zitat Shan, M.K., Kuo, F.F., Chen, M.F.: Music style mining and classification by melody. In: Proceedings of the ICME, vol. 1, pp. 97–100 (2002) Shan, M.K., Kuo, F.F., Chen, M.F.: Music style mining and classification by melody. In: Proceedings of the ICME, vol. 1, pp. 97–100 (2002)
386.
Zurück zum Zitat Shao, X., Xu, C., Kankanhalli, M.S.: Unsupervised classification of music genre using hidden Markov model. In: Proceedings of the ICME, pp. 2023–2026 (2004) Shao, X., Xu, C., Kankanhalli, M.S.: Unsupervised classification of music genre using hidden Markov model. In: Proceedings of the ICME, pp. 2023–2026 (2004)
387.
Zurück zum Zitat Shen, J., Shepherd, J.A., Ngu, A.H.H.: On efficient music genre classification. In: Zhou, L., Ooi, B.-C., Meng, X. (eds.) DASFAA 2005. LNCS, vol. 3453, pp. 253–264. Springer, Heidelberg (2005) Shen, J., Shepherd, J.A., Ngu, A.H.H.: On efficient music genre classification. In: Zhou, L., Ooi, B.-C., Meng, X. (eds.) DASFAA 2005. LNCS, vol. 3453, pp. 253–264. Springer, Heidelberg (2005)
388.
Zurück zum Zitat Shen, J., Shepherd, J., Ngu, A.H.H.: Towards effective content-based music retrieval with multiple acoustic feature combination. IEEE Trans. Multimed. 8(6), 1179–1189 (2006) Shen, J., Shepherd, J., Ngu, A.H.H.: Towards effective content-based music retrieval with multiple acoustic feature combination. IEEE Trans. Multimed. 8(6), 1179–1189 (2006)
389.
Zurück zum Zitat Shen, Y., Li, X., Ma, N.W., Krishnan, S.: Parametric time-frequency analysis and its applications in music classification. EURASIP J. Adv. Signal Process. 2010, 1–9 (2010) Shen, Y., Li, X., Ma, N.W., Krishnan, S.: Parametric time-frequency analysis and its applications in music classification. EURASIP J. Adv. Signal Process. 2010, 1–9 (2010)
390.
Zurück zum Zitat Shih, J.L., Lee, C.H., Lin, S.W.: Automatic classification of musical audio signals. J. Inf. Technol. Appl. 1(2), 95–105 (2006) Shih, J.L., Lee, C.H., Lin, S.W.: Automatic classification of musical audio signals. J. Inf. Technol. Appl. 1(2), 95–105 (2006)
391.
Zurück zum Zitat Silla Jr., C.N., Kaestner, C.A.A., Koerich, A.L.: Time-space ensemble strategies for automatic music genre classification. In: Sichman, J.S., Coelho, H., Rezende, S.O. (eds.) IBERAMIA 2006 and SBIA 2006. LNCS (LNAI), vol. 4140, pp. 339–348. Springer, Heidelberg (2006) Silla Jr., C.N., Kaestner, C.A.A., Koerich, A.L.: Time-space ensemble strategies for automatic music genre classification. In: Sichman, J.S., Coelho, H., Rezende, S.O. (eds.) IBERAMIA 2006 and SBIA 2006. LNCS (LNAI), vol. 4140, pp. 339–348. Springer, Heidelberg (2006)
392.
Zurück zum Zitat Silla, C.N., Koerich, A., Kaestner, C.: Automatic music genre classification using ensembles of classifiers. In: Proceedings of the IEEE International Conference on Systems, Man, Cybernetics, pp. 1687–1692 (2007) Silla, C.N., Koerich, A., Kaestner, C.: Automatic music genre classification using ensembles of classifiers. In: Proceedings of the IEEE International Conference on Systems, Man, Cybernetics, pp. 1687–1692 (2007)
393.
Zurück zum Zitat Silla, C.N., Koerich, A.L., Kaestner, C.A.A.: Feature selection in automatic music genre classification. In: Proceedings of the IEEE International Symposium on Multimedia, pp. 39–44 (2008) Silla, C.N., Koerich, A.L., Kaestner, C.A.A.: Feature selection in automatic music genre classification. In: Proceedings of the IEEE International Symposium on Multimedia, pp. 39–44 (2008)
394.
Zurück zum Zitat Silla, C.N., Koerich, A.L., Kaestner, C.A.A.: The Latin music database. In: Proceedings of the ISMIR (2008) Silla, C.N., Koerich, A.L., Kaestner, C.A.A.: The Latin music database. In: Proceedings of the ISMIR (2008)
395.
Zurück zum Zitat Silla, C., Freitas, A.: Novel top-down approaches for hierarchical classification and their application to automatic music genre classification. In: IEEE International Conference on Systems, Man, and Cybernetics, San Antonio, USA, Oct 2009 Silla, C., Freitas, A.: Novel top-down approaches for hierarchical classification and their application to automatic music genre classification. In: IEEE International Conference on Systems, Man, and Cybernetics, San Antonio, USA, Oct 2009
396.
Zurück zum Zitat Silla, C.N., Koerich, A.L., Kaestner, C.A.A.: A feature selection approach for automatic music genre classification. Int. J. Semantic Comput. 3(2), 183–208 (2009) Silla, C.N., Koerich, A.L., Kaestner, C.A.A.: A feature selection approach for automatic music genre classification. Int. J. Semantic Comput. 3(2), 183–208 (2009)
397.
Zurück zum Zitat Silla, C., Koerich, A., Kaestner, C.: Improving automatic music genre classification with hybrid content-based feature vectors. In: Proceedings of the Symposium on Applied Computer, Sierre, Switzerland, Mar 2010 Silla, C., Koerich, A., Kaestner, C.: Improving automatic music genre classification with hybrid content-based feature vectors. In: Proceedings of the Symposium on Applied Computer, Sierre, Switzerland, Mar 2010
398.
Zurück zum Zitat Silla, C.N., Freitas, A.A.: A survey of hierarchical classification across different application domains. Data Mining Knowl. Disc. 22, 31–72 (2011)MathSciNetMATH Silla, C.N., Freitas, A.A.: A survey of hierarchical classification across different application domains. Data Mining Knowl. Disc. 22, 31–72 (2011)MathSciNetMATH
399.
Zurück zum Zitat Simsekli, U.: Automatic music genre classification using bass lines. In: Proceedings of the ICPR (2010) Simsekli, U.: Automatic music genre classification using bass lines. In: Proceedings of the ICPR (2010)
400.
Zurück zum Zitat Smith, J.B.L., Burgoyne, J.A., Fujinaga, I., Roure, D.D., Downie, J.S.: Design and creation of a large-scale database of structural annotations. In: Proceedings of the ISMIR (2011) Smith, J.B.L., Burgoyne, J.A., Fujinaga, I., Roure, D.D., Downie, J.S.: Design and creation of a large-scale database of structural annotations. In: Proceedings of the ISMIR (2011)
401.
Zurück zum Zitat Soltau, H., Schultz, T., Westphal, M., Waibel, A.: Recognition of music types. In: Proceedings of the ICASSP (1998) Soltau, H., Schultz, T., Westphal, M., Waibel, A.: Recognition of music types. In: Proceedings of the ICASSP (1998)
402.
Zurück zum Zitat Song, Y., Zhang, C., Xiang, S.: Semi-supervised music genre classification. In: Proceedings of the ICASSP, pp. 729–732 (2007) Song, Y., Zhang, C., Xiang, S.: Semi-supervised music genre classification. In: Proceedings of the ICASSP, pp. 729–732 (2007)
403.
Zurück zum Zitat Song, Y., Zhang, C.: Content-based information fusion for semi-supervised music genre classification. IEEE Trans. Multimed. 10(1), 145–152 (2008) Song, Y., Zhang, C.: Content-based information fusion for semi-supervised music genre classification. IEEE Trans. Multimed. 10(1), 145–152 (2008)
404.
Zurück zum Zitat Sordo, M., Celma, O., Blech, M., Guaus, E.: The quest for musical genres: do the experts and the wisdom of crowds agree? In: Proceedings of the ISMIR (2008) Sordo, M., Celma, O., Blech, M., Guaus, E.: The quest for musical genres: do the experts and the wisdom of crowds agree? In: Proceedings of the ISMIR (2008)
405.
Zurück zum Zitat Sotiropoulos, D., Lampropoulos, A., Tsihrintzis, G.: Artificial immune system-based music genre classification. In: Tsihrintzis, G., Virvou, M., Howlett, R., Jain, L. (eds.) New Directions in Intelligent Interactive Multimedia. SCI, vol. 142, pp. 191–200. Springer, Heidelberg (2008) Sotiropoulos, D., Lampropoulos, A., Tsihrintzis, G.: Artificial immune system-based music genre classification. In: Tsihrintzis, G., Virvou, M., Howlett, R., Jain, L. (eds.) New Directions in Intelligent Interactive Multimedia. SCI, vol. 142, pp. 191–200. Springer, Heidelberg (2008)
406.
Zurück zum Zitat Srinivasan, H., Kankanhalli, M.: Harmonicity and dynamics-based features for audio. In: Proceedings of the ICASSP, vol. 4, pp. 321–324 (2004) Srinivasan, H., Kankanhalli, M.: Harmonicity and dynamics-based features for audio. In: Proceedings of the ICASSP, vol. 4, pp. 321–324 (2004)
407.
Zurück zum Zitat Sturm, B.L., Noorzad, P.: On automatic music genre recognition by sparse representation classification using auditory temporal modulations. In: Proceedings of the CMMR, London, UK, June 2012 Sturm, B.L., Noorzad, P.: On automatic music genre recognition by sparse representation classification using auditory temporal modulations. In: Proceedings of the CMMR, London, UK, June 2012
408.
Zurück zum Zitat Sturm, B.L.: An analysis of the GTZAN music genre dataset. In: Proceedings of the ACM MIRUM Workshop, Nara, Japan, Nov 2012 Sturm, B.L.: An analysis of the GTZAN music genre dataset. In: Proceedings of the ACM MIRUM Workshop, Nara, Japan, Nov 2012
409.
Zurück zum Zitat Sturm, B.L.: Two systems for automatic music genre recognition: what are they really recognizing? In: Proceedings of the ACM MIRUM Workshop, Nara, Japan, Nov 2012 Sturm, B.L.: Two systems for automatic music genre recognition: what are they really recognizing? In: Proceedings of the ACM MIRUM Workshop, Nara, Japan, Nov 2012
410.
Zurück zum Zitat Sturm, B.L.: Classification accuracy is not enough: on the analysis of music genre recognition systems. J. Intell. Inf. Syst. 41, 371–406 (2013)MathSciNet Sturm, B.L.: Classification accuracy is not enough: on the analysis of music genre recognition systems. J. Intell. Inf. Syst. 41, 371–406 (2013)MathSciNet
411.
Zurück zum Zitat Sturm, B.L.: On music genre classification via compressive sampling. In: Proceedings of the ICME, July 2013, pp. 1–6 (2013) Sturm, B.L.: On music genre classification via compressive sampling. In: Proceedings of the ICME, July 2013, pp. 1–6 (2013)
412.
Zurück zum Zitat Sturm, B.L.: Music genre recognition with risk and rejection. In: Proceedings of the ICME, July 2013, pp. 1–6 (2013) Sturm, B.L.: Music genre recognition with risk and rejection. In: Proceedings of the ICME, July 2013, pp. 1–6 (2013)
413.
Zurück zum Zitat Su, Z.Y., Wu, T.: Multifractal analyses of music sequences. Phys. D: Nonlin. Phen. 221(2), 188–194 (2006)MathSciNetMATH Su, Z.Y., Wu, T.: Multifractal analyses of music sequences. Phys. D: Nonlin. Phen. 221(2), 188–194 (2006)MathSciNetMATH
414.
Zurück zum Zitat Sundaram, S., Narayanan, S.: Experiments in automatic genre classification of full-length music tracks using audio activity rate. In: Proceedings of the IEEE Workshop Multimedia Signal Processing (2007) Sundaram, S., Narayanan, S.: Experiments in automatic genre classification of full-length music tracks using audio activity rate. In: Proceedings of the IEEE Workshop Multimedia Signal Processing (2007)
415.
Zurück zum Zitat Tacchini, E., Damiani, E.: What is a “musical world”? An affinity propagation approach. In: Proceedings of the ACM MIRUM Workshop, Scottsdale, AZ, USA, pp. 57–62, Nov 2011 Tacchini, E., Damiani, E.: What is a “musical world”? An affinity propagation approach. In: Proceedings of the ACM MIRUM Workshop, Scottsdale, AZ, USA, pp. 57–62, Nov 2011
416.
Zurück zum Zitat Happi Tietche, B., Romain, O., Denby, B., Benaroya, L., Viateur, S.: FPGA-based radio-on-demand broadcast receiver with musical genre identification. In: Proceedings of the IEEE International Symposium on Industrial Electronics, pp. 1381–1385, May 2012 Happi Tietche, B., Romain, O., Denby, B., Benaroya, L., Viateur, S.: FPGA-based radio-on-demand broadcast receiver with musical genre identification. In: Proceedings of the IEEE International Symposium on Industrial Electronics, pp. 1381–1385, May 2012
417.
Zurück zum Zitat Tsai, W.H., Bao, D.F.: Clustering music recordings based on genres. In: Proceedings of the International Conference on Information Science and Applications (2010) Tsai, W.H., Bao, D.F.: Clustering music recordings based on genres. In: Proceedings of the International Conference on Information Science and Applications (2010)
418.
Zurück zum Zitat Tsatsishvili, V.: Automatic subgenre classification of heavy metal music. Master’s thesis, University of Jyväskylä, Nov 2011 Tsatsishvili, V.: Automatic subgenre classification of heavy metal music. Master’s thesis, University of Jyväskylä, Nov 2011
419.
Zurück zum Zitat Tsunoo, E., Tzanetakis, G., Ono, N., Sagayama, S.: Audio genre classification by clustering percussive patterns. In: Proceedings of the Acoustical Society of Japan (2009) Tsunoo, E., Tzanetakis, G., Ono, N., Sagayama, S.: Audio genre classification by clustering percussive patterns. In: Proceedings of the Acoustical Society of Japan (2009)
420.
Zurück zum Zitat Tsunoo, E., Tzanetakis, G., Ono, N., Sagayama, S.: Audio genre classification using percussive pattern clustering combined with timbral features. In: Proceedings of the ICME (2009) Tsunoo, E., Tzanetakis, G., Ono, N., Sagayama, S.: Audio genre classification using percussive pattern clustering combined with timbral features. In: Proceedings of the ICME (2009)
421.
Zurück zum Zitat Tsunoo, E., Tzanetakis, G., Ono, N., Sagayama, S.: Beyond timbral statistics: improving music classification using percussive patterns and bass lines. IEEE Trans. Audio Speech Lang. Process. 19(4), 1003–1014 (2011) Tsunoo, E., Tzanetakis, G., Ono, N., Sagayama, S.: Beyond timbral statistics: improving music classification using percussive patterns and bass lines. IEEE Trans. Audio Speech Lang. Process. 19(4), 1003–1014 (2011)
422.
Zurück zum Zitat Turnbull, D., Elkan, C.: Fast recognition of musical genres using RBF networks. IEEE Trans. Knowl. Data Eng. 17(4), 580–584 (2005) Turnbull, D., Elkan, C.: Fast recognition of musical genres using RBF networks. IEEE Trans. Knowl. Data Eng. 17(4), 580–584 (2005)
423.
Zurück zum Zitat Typke, R., Wiering, F., Veltkamp, R.C.: A survey of music information retrieval systems. In: Proceedings of the ISMIR, London, UK, Sept 2005 Typke, R., Wiering, F., Veltkamp, R.C.: A survey of music information retrieval systems. In: Proceedings of the ISMIR, London, UK, Sept 2005
424.
Zurück zum Zitat Tzagkarakis, C., Mouchtaris, A., Tsakalides, P.: Musical genre classification via generalized Gaussian and alpha-stable modeling. In: Proceedings of the ICASSP, May 2006 Tzagkarakis, C., Mouchtaris, A., Tsakalides, P.: Musical genre classification via generalized Gaussian and alpha-stable modeling. In: Proceedings of the ICASSP, May 2006
425.
Zurück zum Zitat Tzanetakis, G., Essl, G., Cook, P.: Automatic music genre classification of audio signals. In: Proceedings of the ISMIR (2001) Tzanetakis, G., Essl, G., Cook, P.: Automatic music genre classification of audio signals. In: Proceedings of the ISMIR (2001)
426.
Zurück zum Zitat Tzanetakis, G., Cook, P.: Musical genre classification of audio signals. IEEE Trans. Speech Audio Process. 10(5), 293–302 (2002) Tzanetakis, G., Cook, P.: Musical genre classification of audio signals. IEEE Trans. Speech Audio Process. 10(5), 293–302 (2002)
427.
Zurück zum Zitat Tzanetakis, G.: Manipulation, analysis and retrieval systems for audio signals. Ph.D. thesis, Princeton University, June 2002 Tzanetakis, G.: Manipulation, analysis and retrieval systems for audio signals. Ph.D. thesis, Princeton University, June 2002
428.
Zurück zum Zitat Tzanetakis, G., Ermolinskyi, A., Cook, P.: Pitch histograms in audio and symbolic music information retrieval. J. New Music Res. 32(2), 143–152 (2003) Tzanetakis, G., Ermolinskyi, A., Cook, P.: Pitch histograms in audio and symbolic music information retrieval. J. New Music Res. 32(2), 143–152 (2003)
429.
Zurück zum Zitat Umapathy, K., Krishnan, S., Jimaa, S.: Multigroup classification of audio signals using time-frequency parameters. IEEE Trans. Multimed. 7(2), 308–315 (2005) Umapathy, K., Krishnan, S., Jimaa, S.: Multigroup classification of audio signals using time-frequency parameters. IEEE Trans. Multimed. 7(2), 308–315 (2005)
430.
Zurück zum Zitat Valdez, N., Guevara, R.: Feature set for philippine gong music classification by indigenous group. In: Proceedings of the IEEE Region 10 Conference, pp. 339–343, Nov 2011 Valdez, N., Guevara, R.: Feature set for philippine gong music classification by indigenous group. In: Proceedings of the IEEE Region 10 Conference, pp. 339–343, Nov 2011
431.
Zurück zum Zitat Vatolkin, I., Theimer, W.M., Botteck, M.: Partition based feature processing for improved music classification. In: Proceedings of the Annual Conference of the German Classification Society, pp. 411–419 (2010) Vatolkin, I., Theimer, W.M., Botteck, M.: Partition based feature processing for improved music classification. In: Proceedings of the Annual Conference of the German Classification Society, pp. 411–419 (2010)
432.
Zurück zum Zitat Vatolkin, I., Preuß, M., Rudolph, G.: Multi-objective feature selection in music genre and style recognition tasks. In: Genetic and Evolutionary Computation Conference (2011) Vatolkin, I., Preuß, M., Rudolph, G.: Multi-objective feature selection in music genre and style recognition tasks. In: Genetic and Evolutionary Computation Conference (2011)
433.
Zurück zum Zitat Vatolkin, I.: Multi-objective evaluation of music classification. In: Gaul, W.A., Geyer-Schulz, A., Schmidt-Thieme, L., Kunze, J. (eds.) Challenges at the Interface of Data Analysis, Computer Science, and Optimization, pp. 401–410. Springer, Berlin (2012) Vatolkin, I.: Multi-objective evaluation of music classification. In: Gaul, W.A., Geyer-Schulz, A., Schmidt-Thieme, L., Kunze, J. (eds.) Challenges at the Interface of Data Analysis, Computer Science, and Optimization, pp. 401–410. Springer, Berlin (2012)
434.
Zurück zum Zitat Volk, A., van Kranenburg, P.: Melodic similarity among folk songs: an annotation study on similarity-based categorization in music. Musicae Scientiae 16(3), 317–339 (2012) Volk, A., van Kranenburg, P.: Melodic similarity among folk songs: an annotation study on similarity-based categorization in music. Musicae Scientiae 16(3), 317–339 (2012)
435.
Zurück zum Zitat Völkel, T., Abeßer, J., Dittmar, C., Großmann, H.: Automatic genre classification of Latin music using characteristic rhythmic patterns. In: Proceedings of the Audio Mostly Conference, Piteå, Sweden (2010) Völkel, T., Abeßer, J., Dittmar, C., Großmann, H.: Automatic genre classification of Latin music using characteristic rhythmic patterns. In: Proceedings of the Audio Mostly Conference, Piteå, Sweden (2010)
436.
Zurück zum Zitat Wang, L., Huang, S., Wang, S., Liang, J., Xu, B.: Music genre classification based on multiple classifier fusion. In: Proceedings of the International Conference on Natural Computation (2008) Wang, L., Huang, S., Wang, S., Liang, J., Xu, B.: Music genre classification based on multiple classifier fusion. In: Proceedings of the International Conference on Natural Computation (2008)
437.
Zurück zum Zitat Wang, F., Wang, X., Shao, B., Li, T., Ogihara, M.: Tag integrated multi-label music style classification with hypergraph. In: Proceedings of the ISMIR (2009) Wang, F., Wang, X., Shao, B., Li, T., Ogihara, M.: Tag integrated multi-label music style classification with hypergraph. In: Proceedings of the ISMIR (2009)
438.
Zurück zum Zitat Wang, D., Li, T., Ogihara, M.: Are tags better than audio? The effect of joint use of tags and audio content features for artistic style clustering. In: Proceedings of the ISMIR, pp. 57–62 (2010) Wang, D., Li, T., Ogihara, M.: Are tags better than audio? The effect of joint use of tags and audio content features for artistic style clustering. In: Proceedings of the ISMIR, pp. 57–62 (2010)
439.
Zurück zum Zitat Watanabe, S., Nemoto, M.: Reinforcing property of music in Java sparrows (Padda oryzivora). Behav. Process. 43(2), 211–218 (1998) Watanabe, S., Nemoto, M.: Reinforcing property of music in Java sparrows (Padda oryzivora). Behav. Process. 43(2), 211–218 (1998)
440.
Zurück zum Zitat Watanabe, S., Sato, K.: Discriminative stimulus properties of music in Java sparrows. Behav. Process. 47(1), 53–57 (1999)MathSciNet Watanabe, S., Sato, K.: Discriminative stimulus properties of music in Java sparrows. Behav. Process. 47(1), 53–57 (1999)MathSciNet
441.
Zurück zum Zitat Watanabe, S.: How animals perceive music? Comparative study of discriminative and reinforcing properties of music for infrahuman animals. CARLS Series of Advanced Study of Logic and Sensibility vol. 2, pp. 5–16 (2008) Watanabe, S.: How animals perceive music? Comparative study of discriminative and reinforcing properties of music for infrahuman animals. CARLS Series of Advanced Study of Logic and Sensibility vol. 2, pp. 5–16 (2008)
442.
Zurück zum Zitat Weihs, C., Ligges, U., Morchen, F., Mullensiefen, D.: Classification in music research. Adv. Data Anal. Classif. 1(3), 255–291 (2007)MathSciNetMATH Weihs, C., Ligges, U., Morchen, F., Mullensiefen, D.: Classification in music research. Adv. Data Anal. Classif. 1(3), 255–291 (2007)MathSciNetMATH
443.
Zurück zum Zitat Welsh, M., Borisov, N., Hill, J., von Behren, R., Woo, A.: Querying large collections of music for similarity. Technical report, University of California, Berkeley (1999) Welsh, M., Borisov, N., Hill, J., von Behren, R., Woo, A.: Querying large collections of music for similarity. Technical report, University of California, Berkeley (1999)
444.
Zurück zum Zitat West, K., Cox, S.: Features and classifiers for the automatic classification of musical audio signals. In: Proceedings of the ISMIR (2004) West, K., Cox, S.: Features and classifiers for the automatic classification of musical audio signals. In: Proceedings of the ISMIR (2004)
445.
Zurück zum Zitat West, K., Cox, S.: Finding an optimal segmentation for audio genre classification. In: Proceedings of the ISMIR, pp. 680–685 (2005) West, K., Cox, S.: Finding an optimal segmentation for audio genre classification. In: Proceedings of the ISMIR, pp. 680–685 (2005)
446.
Zurück zum Zitat West, K., Lamere, P.: A model-based approach to constructing music similarity functions. EURASIP J. Appl. Signal Process. 1(1), 149 (2007) West, K., Lamere, P.: A model-based approach to constructing music similarity functions. EURASIP J. Appl. Signal Process. 1(1), 149 (2007)
447.
Zurück zum Zitat West, K.: Novel techniques for audio music classification and search. Ph.D. thesis, University of East Anglia (2008) West, K.: Novel techniques for audio music classification and search. Ph.D. thesis, University of East Anglia (2008)
448.
Zurück zum Zitat Whitman, B., Smaragdis, P.: Combining musical and cultural features for intelligent style detection. In: Proceedings of the ISMIR, Paris, France, Oct 2002 Whitman, B., Smaragdis, P.: Combining musical and cultural features for intelligent style detection. In: Proceedings of the ISMIR, Paris, France, Oct 2002
449.
Zurück zum Zitat Wiggins, G.A.: Semantic gap?? Schemantic schmap!! Methodological considerations in the scientific study of music. In: Proceedings of the IEEE International Symposium on Multimedia, pp. 477–482, Dec 2009 Wiggins, G.A.: Semantic gap?? Schemantic schmap!! Methodological considerations in the scientific study of music. In: Proceedings of the IEEE International Symposium on Multimedia, pp. 477–482, Dec 2009
450.
Zurück zum Zitat Wu, M.J., Chen, Z.S., Jang, J.S.R., Ren, J.M.: Combining visual and acoustic features for music genre classification. In: International Conference on Machine Learning and Applications (2011) Wu, M.J., Chen, Z.S., Jang, J.S.R., Ren, J.M.: Combining visual and acoustic features for music genre classification. In: International Conference on Machine Learning and Applications (2011)
451.
Zurück zum Zitat Wülfing, J., Riedmiller, M.: Unsupervised learning of local features for music classification. In: Proceedings of the ISMIR, Porto, Portugal, Oct 2012 Wülfing, J., Riedmiller, M.: Unsupervised learning of local features for music classification. In: Proceedings of the ISMIR, Porto, Portugal, Oct 2012
452.
Zurück zum Zitat Xu, C., Maddage, M., Shao, X., Cao, F., Tian, Q.: Musical genre classification using support vector machines. In: Proceedings of the ICASSP (2003) Xu, C., Maddage, M., Shao, X., Cao, F., Tian, Q.: Musical genre classification using support vector machines. In: Proceedings of the ICASSP (2003)
453.
Zurück zum Zitat Yang, W., Yu, X., Deng, J., Pan, X., Wang, Y.: Audio classification based on fuzzy-rough nearest neighbour clustering. In: Proceedings of the International Conference on Wireless Communications and Mobile Computation, pp. 320–324 (2011) Yang, W., Yu, X., Deng, J., Pan, X., Wang, Y.: Audio classification based on fuzzy-rough nearest neighbour clustering. In: Proceedings of the International Conference on Wireless Communications and Mobile Computation, pp. 320–324 (2011)
454.
Zurück zum Zitat Yang, X., Chen, Q., Zhou, S., Wang, X.: Deep belief networks for automatic music genre classification. In: Proceedings of the INTERSPEECH, pp. 2433–2436 (2011) Yang, X., Chen, Q., Zhou, S., Wang, X.: Deep belief networks for automatic music genre classification. In: Proceedings of the INTERSPEECH, pp. 2433–2436 (2011)
455.
Zurück zum Zitat Yao, Q., Li, H., Sun, J., Ma, L.: Visualized feature fusion and style evaluation for musical genre analysis. In: International Conference on Pervasive Computing, Signal Processing and Applications (2010) Yao, Q., Li, H., Sun, J., Ma, L.: Visualized feature fusion and style evaluation for musical genre analysis. In: International Conference on Pervasive Computing, Signal Processing and Applications (2010)
456.
Zurück zum Zitat Yaslan, Y., Cataltepe, Z.: Audio music genre classification using different classifiers and feature selection methods. In: Proceedings of the ICPR, pp. 573–576 (2006) Yaslan, Y., Cataltepe, Z.: Audio music genre classification using different classifiers and feature selection methods. In: Proceedings of the ICPR, pp. 573–576 (2006)
457.
Zurück zum Zitat Yeh, C.C.M., Yang, Y.H.: Supervised dictionary learning for music genre classification. In: Proceedings of the ACM International Conference on Multimedia Retrieval, Hong Kong, China, June 2012 Yeh, C.C.M., Yang, Y.H.: Supervised dictionary learning for music genre classification. In: Proceedings of the ACM International Conference on Multimedia Retrieval, Hong Kong, China, June 2012
458.
Zurück zum Zitat Ying, T.C., Doraisamy, S., Abdullah, L.N.: Genre and mood classification using lyric features. In: International Conference on Information Retrieval and Knowledge Management (2012) Ying, T.C., Doraisamy, S., Abdullah, L.N.: Genre and mood classification using lyric features. In: International Conference on Information Retrieval and Knowledge Management (2012)
459.
Zurück zum Zitat Yoon, W.-J., Lee, K.-K., Park, K.-S., Yoo, H.-Y.: Automatic classification of western music in digital library. In: Fox, E.A., Neuhold, E.J., Premsmit, P., Wuwongse, V. (eds.) ICADL 2005. LNCS, vol. 3815, pp. 293–300. Springer, Heidelberg (2005) Yoon, W.-J., Lee, K.-K., Park, K.-S., Yoo, H.-Y.: Automatic classification of western music in digital library. In: Fox, E.A., Neuhold, E.J., Premsmit, P., Wuwongse, V. (eds.) ICADL 2005. LNCS, vol. 3815, pp. 293–300. Springer, Heidelberg (2005)
460.
Zurück zum Zitat Zanoni, M., Ciminieri, D., Sarti, A., Tubaro, S.: Searching for dominant high-level features for music information retrieval. In: Proceedings of the EUSIPCO, Bucharest, Romania, pp. 2025–2029, Aug 2012 Zanoni, M., Ciminieri, D., Sarti, A., Tubaro, S.: Searching for dominant high-level features for music information retrieval. In: Proceedings of the EUSIPCO, Bucharest, Romania, pp. 2025–2029, Aug 2012
461.
Zurück zum Zitat Zeng, Z., Zhang, S., Li, H., Liang, W., Zheng, H.: A novel approach to musical genre classification using probabilistic latent semantic analysis model. In: Proceedings of the ICME, pp. 486–489 (2009) Zeng, Z., Zhang, S., Li, H., Liang, W., Zheng, H.: A novel approach to musical genre classification using probabilistic latent semantic analysis model. In: Proceedings of the ICME, pp. 486–489 (2009)
462.
Zurück zum Zitat Zhang, Y., Zhou, J.: A study on content-based music classification. In: Proceedings of the International Symposium on Signal Processing and Its Applications, pp. 113–116, July 2003 Zhang, Y., Zhou, J.: A study on content-based music classification. In: Proceedings of the International Symposium on Signal Processing and Its Applications, pp. 113–116, July 2003
463.
Zurück zum Zitat Zhang, Y.B., Zhou, J., Wang, X.: A study on Chinese traditional opera. In: Proceedings of the International Conference on Machine Learning and Cybernetics, pp. 2476–2480, July 2008 Zhang, Y.B., Zhou, J., Wang, X.: A study on Chinese traditional opera. In: Proceedings of the International Conference on Machine Learning and Cybernetics, pp. 2476–2480, July 2008
464.
Zurück zum Zitat Zhen, C., Xu, J.: Solely tag-based music genre classification. In: Proceedings of the International Conference on Web Information Systems and Mining (2010) Zhen, C., Xu, J.: Solely tag-based music genre classification. In: Proceedings of the International Conference on Web Information Systems and Mining (2010)
465.
Zurück zum Zitat Zhen, C., Xu, J.: Multi-modal music genre classification approach. In: Proceedings of the IEEE International Conference on Computer Science and Information Technology (2010) Zhen, C., Xu, J.: Multi-modal music genre classification approach. In: Proceedings of the IEEE International Conference on Computer Science and Information Technology (2010)
466.
Zurück zum Zitat Zhou, G.T., Ting, K.M., Liu, F.T., Yin, Y.: Relevance feature mapping for content-based multimedia information retrieval. Pattern Recogn. 45, 1707–1720 (2012) Zhou, G.T., Ting, K.M., Liu, F.T., Yin, Y.: Relevance feature mapping for content-based multimedia information retrieval. Pattern Recogn. 45, 1707–1720 (2012)
467.
Zurück zum Zitat Zhu, J., Xue, X., Lu, H.: Musical genre classification by instrumental features. In: Proceedings of the ICMC (2004) Zhu, J., Xue, X., Lu, H.: Musical genre classification by instrumental features. In: Proceedings of the ICMC (2004)
468.
Zurück zum Zitat Fabbri, F.: A theory of musical genres: two applications. In: Proceedings of the International Conference on Popular Music Studies, Amsterdam, The Netherlands (1980) Fabbri, F.: A theory of musical genres: two applications. In: Proceedings of the International Conference on Popular Music Studies, Amsterdam, The Netherlands (1980)
469.
Zurück zum Zitat Frow, J.: Genre. Routledge, New York (2005) Frow, J.: Genre. Routledge, New York (2005)
470.
Zurück zum Zitat Bertin-Mahieux, T., Eck, D., Mandel, M.: Automatic tagging of audio: the state-of-the-art. In: Wang, W. (ed.) Machine Audition: Principles, Algorithms and Systems. IGI Publishing, Hershey (2010) Bertin-Mahieux, T., Eck, D., Mandel, M.: Automatic tagging of audio: the state-of-the-art. In: Wang, W. (ed.) Machine Audition: Principles, Algorithms and Systems. IGI Publishing, Hershey (2010)
471.
Zurück zum Zitat Kim, Y., Schmidt, E., Migneco, R., Morton, B., Richardson, P., Scott, J., Speck, J., Turnbull, D.: Music emotion recognition: a state of the art review. In: Proceedings of the ISMIR, pp. 255–266 (2010) Kim, Y., Schmidt, E., Migneco, R., Morton, B., Richardson, P., Scott, J., Speck, J., Turnbull, D.: Music emotion recognition: a state of the art review. In: Proceedings of the ISMIR, pp. 255–266 (2010)
472.
Zurück zum Zitat Soltau, H.: Erkennung von Musikstilen. Ph.D. thesis, Universität Karlsruhe, Karlsruhe, Germany, May 1997 Soltau, H.: Erkennung von Musikstilen. Ph.D. thesis, Universität Karlsruhe, Karlsruhe, Germany, May 1997
473.
Zurück zum Zitat Kiernan, F.J.: Score-based style recognition using artificial neural networks. In: Proceedings of the ISMIR (2000) Kiernan, F.J.: Score-based style recognition using artificial neural networks. In: Proceedings of the ISMIR (2000)
474.
Zurück zum Zitat Avcu, N., Kuntalp, D., Alpkocak, V.A.: Musical genre classification using higher-order statistics. In: Proceedings of the IEEE Signal Processing and Communication Applications Conference, pp. 1–4, June 2007 Avcu, N., Kuntalp, D., Alpkocak, V.A.: Musical genre classification using higher-order statistics. In: Proceedings of the IEEE Signal Processing and Communication Applications Conference, pp. 1–4, June 2007
475.
Zurück zum Zitat Bagci, U., Erzin, E.: Inter genre similarity modeling for automatic music genre classification. In: Proceedings of the IEEE Signal Processing and Communications Applications, pp. 1–4, Apr 2006 Bagci, U., Erzin, E.: Inter genre similarity modeling for automatic music genre classification. In: Proceedings of the IEEE Signal Processing and Communications Applications, pp. 1–4, Apr 2006
476.
Zurück zum Zitat Herkiloglu, K., Gursoy, O., Gunsel, B.: Music genre determination using audio fingerprinting. In: Proceedings of the IEEE Signal Processing and Communications Applications, pp. 1–4, Apr 2006 Herkiloglu, K., Gursoy, O., Gunsel, B.: Music genre determination using audio fingerprinting. In: Proceedings of the IEEE Signal Processing and Communications Applications, pp. 1–4, Apr 2006
477.
Zurück zum Zitat Sonmez, A.: Music genre and composer identification by using Kolmogorov distance. Master’s thesis, Istanbul Technical University, Istanbul, Turkey (2005) Sonmez, A.: Music genre and composer identification by using Kolmogorov distance. Master’s thesis, Istanbul Technical University, Istanbul, Turkey (2005)
478.
Zurück zum Zitat Yaslan, Y., Cataltepe, Z.: Music genre classification using audio features, different classifiers and feature selection methods. In: Proceedings of the IEEE Signal Processing and Communications Applications, pp. 1–4, Apr 2006 Yaslan, Y., Cataltepe, Z.: Music genre classification using audio features, different classifiers and feature selection methods. In: Proceedings of the IEEE Signal Processing and Communications Applications, pp. 1–4, Apr 2006
479.
Zurück zum Zitat Yaslan, Y., Cataltepe, Z.: Audio genre classification with co-MRMR. In: Proceedings of the IEEE Signal Processing and Communications Applications, pp. 408–411, Apr 2009 Yaslan, Y., Cataltepe, Z.: Audio genre classification with co-MRMR. In: Proceedings of the IEEE Signal Processing and Communications Applications, pp. 408–411, Apr 2009
480.
Zurück zum Zitat Allamanche, E., Kastner, T., Wistorf, R., Lefebvre, N., Herre, J.: Music genre estimation from low level audio features. In: Proceedings of the International Audio Engineering Society Conference (2004) Allamanche, E., Kastner, T., Wistorf, R., Lefebvre, N., Herre, J.: Music genre estimation from low level audio features. In: Proceedings of the International Audio Engineering Society Conference (2004)
481.
Zurück zum Zitat Seo, J.S.: An informative feature selection method for music genre classification. Trans. Japanese Eng. Tech. Org. 94–D(6), 1362–1365 (2011) Seo, J.S.: An informative feature selection method for music genre classification. Trans. Japanese Eng. Tech. Org. 94–D(6), 1362–1365 (2011)
482.
Zurück zum Zitat Berenzweig, A., Logan, B., Ellis, D.P.W., Whitman, B.: A large-scale evaluation of acoustic and subjective music-similarity measures. Comput. Music J. 28(2), 63–76 (2004) Berenzweig, A., Logan, B., Ellis, D.P.W., Whitman, B.: A large-scale evaluation of acoustic and subjective music-similarity measures. Comput. Music J. 28(2), 63–76 (2004)
483.
Zurück zum Zitat Goto, M., Hashiguchi, H., Nishimura, T., Oka, R.: RWC music database: music genre database and musical instrument sound database. In: Proceedings of the ISMIR (2003) Goto, M., Hashiguchi, H., Nishimura, T., Oka, R.: RWC music database: music genre database and musical instrument sound database. In: Proceedings of the ISMIR (2003)
484.
Zurück zum Zitat Bertin-Mahieux, T., Ellis, D.P., Whitman, B., Lamere, P.: The million song dataset. In: Proceedings of the ISMIR (2011) Bertin-Mahieux, T., Ellis, D.P., Whitman, B., Lamere, P.: The million song dataset. In: Proceedings of the ISMIR (2011)
485.
Zurück zum Zitat Law, E.: Human computation for music classification. In: Li, T., Ogihara, M., Tzanetakis, G. (eds.) Music Data Mining, pp. 281–301. CRC Press, Boca Raton (2011) Law, E.: Human computation for music classification. In: Li, T., Ogihara, M., Tzanetakis, G. (eds.) Music Data Mining, pp. 281–301. CRC Press, Boca Raton (2011)
Metadaten
Titel
A Survey of Evaluation in Music Genre Recognition
verfasst von
Bob L. Sturm
Copyright-Jahr
2014
DOI
https://doi.org/10.1007/978-3-319-12093-5_2

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