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2016 | OriginalPaper | Chapter

Key Estimation in Electronic Dance Music

Authors : Ángel Faraldo, Emilia Gómez, Sergi Jordà, Perfecto Herrera

Published in: Advances in Information Retrieval

Publisher: Springer International Publishing

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Abstract

In this paper we study key estimation in electronic dance music, an umbrella term referring to a variety of electronic music subgenres intended for dancing at nightclubs and raves. We start by defining notions of tonality and key before outlining the basic architecture of a template-based key estimation method. Then, we report on the tonal characteristics of electronic dance music, in order to infer possible modifications of the method described. We create new key profiles combining these observations with corpus analysis, and add two pre-processing stages to the basic algorithm. We conclude by comparing our profiles to existing ones, and testing our modifications on independent datasets of pop and electronic dance music, observing interesting improvements in the performance or our algorithms, and suggesting paths for future research.

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Footnotes
1
We take this term from Tagg [26] to refer to European Classical Music of the so-called common practice repertoire, on which most treatises on harmony are based.
 
2
The Music Information Retrieval Evaluation eXchange (MIREX) is an international committee born to evaluate advances in Music Information Retrieval among different research centres, by quantitatively comparing algorithm performance using test sets that are not available beforehand to participants.
 
7
After informal testing, we decided to use the following settings in all the experiments reported: mix-down to mono; sampling rate: 44,100 Hz.; window size: 4,096 hanning; hop size: 16,384; frequency range: 25–3,500 Hz.; PCP size: 36 bins; weighting size: 1 semitone; similarity: cosine distance.
 
Literature
1.
go back to reference Bogdanov, D., Wack, N., Gómez, E., Gulati, S., Herrera, P., Mayor, O.: ESSENTIA: an open-source library for sound and music analysis. In: Proceedings 21st ACM-ICM, pp. 855–858 (2013) Bogdanov, D., Wack, N., Gómez, E., Gulati, S., Herrera, P., Mayor, O.: ESSENTIA: an open-source library for sound and music analysis. In: Proceedings 21st ACM-ICM, pp. 855–858 (2013)
3.
go back to reference Everett, W.: Making sense of rock’s tonal systems. Music Theory Online, vol. 10(4) (2004) Everett, W.: Making sense of rock’s tonal systems. Music Theory Online, vol. 10(4) (2004)
4.
go back to reference Dayal, G., Ferrigno, E.: Electronic Dance Music. Grove Music Online. Oxford University Press, Oxford (2012) Dayal, G., Ferrigno, E.: Electronic Dance Music. Grove Music Online. Oxford University Press, Oxford (2012)
5.
go back to reference Dressler, K., Streich, S.: Tuning frequency estimation using circular statistics. In: Proceedings of the 8th ISMIR, pp. 2–5 (2007) Dressler, K., Streich, S.: Tuning frequency estimation using circular statistics. In: Proceedings of the 8th ISMIR, pp. 2–5 (2007)
6.
go back to reference Gómez, E.: Tonal description of polyphonic audio for music content processing. INFORMS J. Comput. 18(3), 294–304 (2006)CrossRef Gómez, E.: Tonal description of polyphonic audio for music content processing. INFORMS J. Comput. 18(3), 294–304 (2006)CrossRef
7.
go back to reference Gómez, E.: Tonal description of music audio signals. Ph.D. thesis, Universitat Pompeu Fabra, Barcelona (2006) Gómez, E.: Tonal description of music audio signals. Ph.D. thesis, Universitat Pompeu Fabra, Barcelona (2006)
8.
go back to reference Harte., C.: Towards automatic extraction of harmony information from music signals. Ph.D. thesis, Queen Mary University of London (2010) Harte., C.: Towards automatic extraction of harmony information from music signals. Ph.D. thesis, Queen Mary University of London (2010)
9.
go back to reference Hyer, B.: Tonality. Grove Music Online. Oxford University Press, Oxford (2012) Hyer, B.: Tonality. Grove Music Online. Oxford University Press, Oxford (2012)
11.
go back to reference Klapuri, A.: Multipitch analysis of polyphonic music and speech signals using an auditory model. IEEE Trans. Audio Speech Lang. Process. 16(2), 255–266 (2008)CrossRef Klapuri, A.: Multipitch analysis of polyphonic music and speech signals using an auditory model. IEEE Trans. Audio Speech Lang. Process. 16(2), 255–266 (2008)CrossRef
12.
go back to reference Knees, P., Faraldo, Á., Herrera, P., Vogl, R., Böck, S., Hörschläger, F., Le Goff, M.: Two data sets for tempo estimation and key detection in electronic dance music annotated from user corrections. In: Proceeings of the 16th ISMIR (2015) Knees, P., Faraldo, Á., Herrera, P., Vogl, R., Böck, S., Hörschläger, F., Le Goff, M.: Two data sets for tempo estimation and key detection in electronic dance music annotated from user corrections. In: Proceeings of the 16th ISMIR (2015)
13.
go back to reference Krumhansl, C.L.: Cognitive Foundations of Musical Pitch. Oxford Unversity Press, New York (1990) Krumhansl, C.L.: Cognitive Foundations of Musical Pitch. Oxford Unversity Press, New York (1990)
14.
go back to reference Mauch, M., Dixon., S.: Approximate note transcription for the improvedidentification of difficult chords. In: Proceedings of the 11th ISMIR, pp. 135–140 (2010) Mauch, M., Dixon., S.: Approximate note transcription for the improvedidentification of difficult chords. In: Proceedings of the 11th ISMIR, pp. 135–140 (2010)
15.
go back to reference Mauch, M., Cannam, C., Davies, M., Dixon, S., Harte, C., Kolozali, S., Tidjar, D.: OMRAS2 metadata project 2009. In: Proceedings of the 10th ISMIR, Late-Breaking Session (2009) Mauch, M., Cannam, C., Davies, M., Dixon, S., Harte, C., Kolozali, S., Tidjar, D.: OMRAS2 metadata project 2009. In: Proceedings of the 10th ISMIR, Late-Breaking Session (2009)
16.
go back to reference Moore, A.: The so-called “flattened seventh” in rock. Pop. Music 14(2), 185–201 (1995)CrossRef Moore, A.: The so-called “flattened seventh” in rock. Pop. Music 14(2), 185–201 (1995)CrossRef
17.
go back to reference Müller, M., Ewert, S.: Towards timbre-invariant audio features for harmony-based music. IEEE Trans. Audio Speech Lang. Process. 18(3), 649–662 (2010)CrossRef Müller, M., Ewert, S.: Towards timbre-invariant audio features for harmony-based music. IEEE Trans. Audio Speech Lang. Process. 18(3), 649–662 (2010)CrossRef
18.
go back to reference Noland, K.: Computational Tonality estimation: Signal Processing and Hidden Markov Models. Ph.D. thesis, Queen Mary University of London (2009) Noland, K.: Computational Tonality estimation: Signal Processing and Hidden Markov Models. Ph.D. thesis, Queen Mary University of London (2009)
19.
go back to reference Noland, K., Sandler, M.: Signal processing parameters for tonality estimation. In: Proceedings of the 122nd Convention Audio Engeneering Society (2007) Noland, K., Sandler, M.: Signal processing parameters for tonality estimation. In: Proceedings of the 122nd Convention Audio Engeneering Society (2007)
21.
go back to reference Saslaw, J.: Modulation (i). Grove Music Online. Oxford University Press, Oxford (2012) Saslaw, J.: Modulation (i). Grove Music Online. Oxford University Press, Oxford (2012)
22.
go back to reference Schellenberg, E.G., von Scheve, C.: Emotional cues in American popular music: five decades of the Top 40. Psychol. Aesthetics Creativity Arts 6(3), 196–203 (2012)CrossRef Schellenberg, E.G., von Scheve, C.: Emotional cues in American popular music: five decades of the Top 40. Psychol. Aesthetics Creativity Arts 6(3), 196–203 (2012)CrossRef
23.
go back to reference Sha’ath., I.: Estimation of key in digital music recordings. In: Departments of Computer Science & Information Systems, Birkbeck College, University of London (2011) Sha’ath., I.: Estimation of key in digital music recordings. In: Departments of Computer Science & Information Systems, Birkbeck College, University of London (2011)
24.
go back to reference Spicer, M.: (Ac)cumulative form in pop-rock music. Twentieth Century Music 1(1), 29–64 (2004)CrossRef Spicer, M.: (Ac)cumulative form in pop-rock music. Twentieth Century Music 1(1), 29–64 (2004)CrossRef
25.
go back to reference Tagg, P.: From refrain to rave: the decline of figure and raise of ground. Pop. Music 13(2), 209–222 (1994)CrossRef Tagg, P.: From refrain to rave: the decline of figure and raise of ground. Pop. Music 13(2), 209–222 (1994)CrossRef
26.
go back to reference Tagg., P.: Everyday tonality II (Towards a tonal theory of what most people hear). The Mass Media Music Scholars’ Press. New York and Huddersfield (2014) Tagg., P.: Everyday tonality II (Towards a tonal theory of what most people hear). The Mass Media Music Scholars’ Press. New York and Huddersfield (2014)
27.
go back to reference Temperley, D.: What’s key for key? The Krumhansl-Schmuckler key-finding algorithm reconsidered. Music Percept. Interdiscip. J. 17(1), 65–100 (1999)CrossRef Temperley, D.: What’s key for key? The Krumhansl-Schmuckler key-finding algorithm reconsidered. Music Percept. Interdiscip. J. 17(1), 65–100 (1999)CrossRef
28.
go back to reference Röbel, A., Rodet, X.: Efficient spectral envelope estimation and its application to pitch shifting and envelope preservation. In: Proceedings of the 8th DAFX (2005) Röbel, A., Rodet, X.: Efficient spectral envelope estimation and its application to pitch shifting and envelope preservation. In: Proceedings of the 8th DAFX (2005)
29.
go back to reference Zhu, Y., Kankanhalli, M.S., Gao., S.: Music key detection for musical audio. In: Proceedings of the 11th IMMC, pp. 30–37 (2005) Zhu, Y., Kankanhalli, M.S., Gao., S.: Music key detection for musical audio. In: Proceedings of the 11th IMMC, pp. 30–37 (2005)
Metadata
Title
Key Estimation in Electronic Dance Music
Authors
Ángel Faraldo
Emilia Gómez
Sergi Jordà
Perfecto Herrera
Copyright Year
2016
Publisher
Springer International Publishing
DOI
https://doi.org/10.1007/978-3-319-30671-1_25