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Articles

Perception of Timbre and Rhythm Similarity in Electronic Dance Music

, , , &
Pages 373-390 | Received 05 Jun 2015, Accepted 07 Oct 2015, Published online: 10 Nov 2015

References

  • Alluri, V., & Toiviainen, P. (2010). Exploring perceptual and acoustical correlates of polyphonic timbre. Music Perception, 27(3), 223–242.
  • Aucouturier, J.-J., Pachet, F., & Sandler, M. (2005). The way it sounds: Timbre models for analysis and retrieval of music signals. IEEE Transactions on Multimedia, 7(6), 1–8.
  • Berenzweig, A., Logan, B., Ellis, D.P., & Whitman, B. (2004). A large-scale evaluation of acoustic and subjective music-similarity measures. Computer Music Journal, 28(2), 63–76.
  • Boersma, P., & Weenink, D. (2015). Praat: Doing phonetics by computer [Computer program] (Version 5.4.16). Retrieved 16 August 2015 from http://www.praat.org/
  • Bregman, A.S. (1994). Auditory scene analysis: The perceptual organization of sound. Cambridge, MA: MIT Press.
  • Butler, M.J. (2006). Unlocking the groove: Rhythm, meter, and musical design in electronic dance music. Washington, DC: Georgetown University Press.
  • Cambouropoulos, E. (2009). How similar is similar? Musicae Scientiae, 13(1), 7–24.
  • Cao, E., Lotstein, M., & Johnson-Laird, P.N. (2014). Similarity and families of musical rhythms. Music Perception: An Interdisciplinary Journal, 31(5), 444–469.
  • Chew, E., Volk, A., & Lee, C.Y. (2005). Dance music classification using inner metric analysis. In The next wave in computing, optimization, and decision technologies (pp. 355–370). Berlin: Springer.
  • Collins, N. (2012). Influence in early electronic dance music: An audio content analysis investigation. In Proceedings of the International Society for Music Information Retrieval (ISMIR) (pp. 1–6). Canada: International Society for Music Information Retrieval.
  • Collins, N., Schedel, M., & Wilson, S. (2013). Electronic dance music. Electronic music ( Chapter 8, pp. 102–119, Cambridge Introductions to Music Series). Cambridge: Cambridge University Press.
  • Dayal, G., & Ferrigno, E. (2014). Electronic dance music. Oxford: Oxford University Press.
  • Downie, J.S., Lee, J.H., Gruzd, A.A., & Jones, M.C. (2007). Toward an understanding of similarity judgments for music digital library evaluation. In Proceedings of the 7th ACM/IEEE-CS joint conference on digital libraries (pp. 307–308). New York: ACM.
  • Fleiss, J.L. (1971). Measuring nominal scale agreement among many raters. Psychological Bulletin, 76(5), 378.
  • Ghias, A., Logan, J., Chamberlin, D., & Smith, B.C. (1995). Query by humming: musical information retrieval in an audio database. In Proceedings of the third ACM international conference on multimedia (pp. 231–236). New York: ACM.
  • Guastavino, C., Gomez, F., Toussaint, G., Marandola, F., & Gómez, E. (2009). Measuring similarity between flamenco rhythmic patterns. Journal of New Music Research, 38(2), 129–138.
  • Handel, S. (1992). The differentiation of rhythmic structure. Perception & Psychophysics, 52(5), 497–507.
  • Honing, H. (2013). The structure and interpretation of rhythm in music. In D. Deutsch (Ed.), Psychology of music (pp. 369–404). New York: Academic Press.
  • Jones, M.C., Downie, J.S., & Ehmann, A.F. (2007). Human similarity judgments: Implications for the design of formal evaluations. In Proceedings of the International Society for Music Information Retrieval (ISMIR) (pp. 539–542). Vienna: Austrian Computer Society (OCG).
  • Landis, J.R., & Koch, G. G. (1977). The measurement of observer agreement for categorical data. Biometrics, 33(1), 159–174.
  • Lartillot, O., Eerola, T., Toiviainen, P., & Fornari, J. (2008). Multi-feature modeling of pulse clarity: Design, validation and optimization. Proceedings of the International Society for Music Information Retrieval (ISMIR). Canada: International Society for Music Information Retrieval. (pp. 521–526)
  • McLeod, K. (2001). Genres, subgenres, sub-subgenres and more: Musical and social differentiation within electronic/dance music communities. Journal of Popular Music Studies, 13(1), 59–75.
  • Nagavi, T.C., & Bhajantri, N.U. (2014). Progressive filtering approach for query by humming system through empirical mode decomposition and multiresolution histograms. Journal of Intelligent Systems, 24(2), 265–275.
  • Novello, A., McKinney, M. M., & Kohlrausch, A. (2011). Perceptual evaluation of inter-song similarity in western popular music. Journal of New Music Research, 40(1), 1–26.
  • Novello, A., van de Par, S., McKinney, M. M., & Kohlrausch, A. (2013). Algorithmic prediction of inter-song similarity in western popular music. Journal of New Music Research, 42(1), 27–45.
  • Pachet, F., & Aucouturier, J.-J. (2004). Improving timbre similarity: How high is the sky? Journal of Negative Results in Speech and Audio Sciences, 1(1), 1–13.
  • Pampalk, E. (2004). A Matlab toolbox to compute music similarity from audio. Proceedings of the International Society for Music Information Retrieval (ISMIR) (4pp). Barcelona: Universitat Pompeu Fabr.
  • Panteli, M., Bogaards, N., & Honingh, A. (2014). Modeling rhythm similarity for electronic dance music. In Proceedings of the International Society for Music Information Retrieval (ISMIR) (pp. 537–542). Canada: International Society for Music Information Retrieval.
  • Paulus, J., & Klapuri, A. (2002). Measuring the similarity of rhythmic patterns. In Proceedings of the International Society for Music Information Retrieval (ISMIR) (7pp). Paris: IRCAM - - Centre Pompidou.
  • Reynolds, S. (2008). Energy flash: A journey through rave music and dance culture (2nd ed.). London: Picador.
  • Schedl, M., & Knees, P. (2013). Personalization in multimodal music retrieval. In Adaptive multimedia retrieval. Large-scale multimedia retrieval and evaluation (pp. 58–71). Berlin: Springer.
  • Schnitzer, D., Flexer, A., & Widmer, G. (2012). A fast audio similarity retrieval method for millions of music tracks. Multimedia Tools and Applications, 58(1), 23–40.
  • Wolff, D., & Weyde, T. (2014). Learning music similarity from relative user ratings. Information Retrieval, 17(2), 109–136.
  • Yeston, M. (1976). The stratification of musical rhythm. New Haven, CT: Yale University Press.

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