Alberto Pinto
Abstract
The increasing diffusion of XML languages for the encoding of domain-specific multimedia information raises the need for new information retrieval models that can fully exploit structural information. An XML language specifically designed for music like MX allows queries to be made directly on the thematic material. The main advantage of such a system is that it can handle symbolic, notational, and audio objects at the same time through a multilayered structure. On the model side, common music information retrieval methods do not take into account the inner structure of melodic themes and the metric relationships between notes.
In this article we deal with two main topics: a novel architecture based on a new XML language for music and a new model of melodic themes based on graph theory.
This model takes advantage of particular graph invariants that can be linked to melodic themes as metadata in order to characterize all their possible modifications through specific transformations and that can be exploited in filtering algorithms. We provide a similarity function and show through an evaluation stage how it improves existing methods, particularly in the case of same-structured themes.
- Aucouturier, J.-J. and Pachet, F. 2003. Respresenting musial genre: A state of the art. J. New Music Res. 32, 83--93.Google Scholar
Cross Ref
- Bach, J. S. 1976. Orgelwerke. Peters, Leipzig, Germany.Google Scholar
- Baeza-Yates, R. and Ribeiro-Neto, B. 1999. Modern Information Retrieval. Addison-Wesley-Longman. Google ScholarDigital Library
- Baroni, M., Dalmonte, R., and Jacoboni, C. 1999. Le Regole Della Musica. EDT, Torino, Italy.Google Scholar
- Bollobás, B. 1998. Modern Graph Theory. Springer, New York.Google Scholar
- Buckley, F. and Harary, F. 1990. Distance in Graphs. Addison-Wesley.Google Scholar
- Diana, L. 2004. An XML-based querying model for MIR applications within a multilayered music information environment. Ph.D. thesis, Università degli Studi di Milano, Milano, I 20135. Also available as Università degli Studi di Milano, Department of Computer Science Rep.Google Scholar
- Godsil, C. and Royle, G. 2001. Algebraic Graph Theory. Graduate Texts in Mathematics, vol. 207, Springer.Google Scholar
- Good, M. 2001. MusicXML for notation and analysis. In The VirtualScore: Representation, Retrieval, Restoration. MIT Press, Cambridge, MA, 113--124.Google Scholar
- Haus, G. 1984. Elementi di Informatica Musicale. Jackson, Milano, Italy.Google Scholar
- Haus, G. and Longari, M. 2005. A multi-layered, timebased music description approach based on XML. Comput. Music J. 29, 1 (Feb.), 70--85. Google ScholarDigital Library
- Haus, G., Longari, M., and Pollastri, E. 2004. A score-driven approach to music information retrieval. J. Amer. Soc. Inf. Sci. Technol. 55, 12, 1045--1052. Google ScholarDigital Library
- Haus, G. and Pollastri, E. 2000. A multimodal framework for music inputs (poster session). In Proceedings of the 8th International Conference on ACM, Multimedia. 382--384. Google ScholarDigital Library
- Haus, G. and Sametti, A. 1991. Scoresynth: A system for the synthesis of music scores based on petri nets and a music algebra. IEEE Comput. 24, 7, 56--60. Google ScholarDigital Library
- Hewlett, W. B. and Selfridge-Field, E. 2000. Melodic similarity: Concepts, procedures, and applications. In Computing in Musicology, vol. 11. MIT Press, Cambridge, MA, 113--124.Google Scholar
- Hewlett, W. B. and Selfridge-Field, E. 2005. Music Query. MIT Press, Cambridge, MA.Google Scholar
- Lerdahl, F. and Jackendoff, R. 1996. A Generative Theory of Tonal Music. MIT Press, Cambridge, MA.Google Scholar
- Longari, M. 2004. Formal and software tools for a commonly acceptable musical application using the XML language. Ph.D. thesis, Università degli Studi di Milano, Milano, IT 20135. Also available as Università degli Studi di Milano, Department of Computer Science Rep.Google Scholar
- Mongeau, M. and Sankoff, D. 1990. Comparison of musical sequences. Comput. Humanities 24, 3, 161--175.Google ScholarCross Ref
- Pinto, A. 2003. Modelli formali per misure di similarità musicale. M.S. thesis, Università degli Studi di Milano, Milano I 20135. Also available as Università degli Studi di Milano, Department of Mathematics Rep.Google Scholar
- Polansky, L. 1992. More on morphological mutation functions: Recent techniques and developements. In Proceedings of the International Computer Music Conference.Google Scholar
- Polansky, L. 1996. Morphological metrics. J. New Music Res. 25, 289--368.Google ScholarCross Ref
- Roads, C. 1996. The Computer Music Tutorial. MIT Press, Cambridge, MA. Google ScholarDigital Library
- Schoenberg, A. 1911. Harmonielehre. Universal Edition, Leipzig, Germany.Google Scholar
- Tenney, J. and Polansky, L. 1980. Temporal gestalt perception in music: A metric space model. J. Music Theory 24, 2, 205--41.Google ScholarCross Ref
- Tsinaraki, C., Polydoros, P., and Christodoulakis, S. 2004. Integration of OWL ontologies in MPEG-7 and TV-anytime compliant semantic indexing. In (HDMS) the Hellenic Data Management Symposium.Google Scholar
- Verdi, L. 1998. Organizzazione delle altezze nello spazio temperato. In Ensemble '900 (Treviso, Italy).Google Scholar
Index Terms
- A novel XML music information retrieval method using graph invariants
Recommendations
Music Genre Classification and Feature Comparison using ML
ICMLT '22: Proceedings of the 2022 7th International Conference on Machine Learning TechnologiesAn essential feature of the music is the genre, which can be considered a high-level description of an individual piece of music. In this sense, genre as a music feature is similar to typical descriptive features from the ML perspective. Although a ...
Pitch-frequency histogram-based music information retrieval for Turkish music
This study reviews the use of pitch histograms in music information retrieval studies for western and non-western music. The problems in applying the pitch-class histogram-based methods developed for western music to non-western music and specifically ...
Interactive music 3.0: empowering people to participate musically inside nightclubs
CMMR'11: Proceedings of the 8th international conference on Speech, Sound and Music Processing: embracing research in IndiaNightclubs are powerhouses in western culture for social listening and dancing to music. Here, mostly digital, pre-composed tunes are selected, mixed and played by a person called Disc Jockey. In another digital arena, the internet, a revolution is ...
Comments