684
Views
37
CrossRef citations to date
0
Altmetric
Articles

Classification of Melodic Motifs in Raga Music with Time-series Matching

, , , , , & show all
Pages 115-131 | Received 09 Jun 2013, Accepted 04 Dec 2013, Published online: 31 Mar 2014

References

  • Berndt, D., & Clifford, J. (1994). Using dynamic time warping to find patterns in time series. In KDD-94 workshop on knowledge discovery in databases, Seattle, Washington, July (Vol. 10, 16, pp. 359–370). Palo Alto, CA: AAAI.
  • Cambouropoulos, E. (2006). Musical parallelism and melodic segmentation: A omputational approach. Music Perception, 23(3), 249–268.
  • Chakravorty, J., Mukherjee, B., & Datta, A.K. (1989). Some studies in machine recognition of ragas in Indian classical music. Journal of the Acoustical Society of India, 17(3 &4).
  • Chordia, P., & Rae, A. (2007). Raag recognition using pitch-class and pitch-class dyad distributions. In Proceedings of International Conference on Music Information Retrieval, Vienna, Austria September (pp. 1–6). Vienna: Austrian Computer Society (OCG).
  • Dannenberg, R.B., & Hu, N. (2003). Pattern discovery techniques for music audio. Journal of New Music Research, 32(2), 153–163.
  • Ishwar, V., Dutta, S., Bellur, A., & Murthy, H. (2013). Motif spotting in an alapana in Carnatic music. In Proceedings of the Conference of the International Society for Music Information Retrieval Conference, Curitiba, Brazil.
  • Juhász, Z. (2007). Analysis of melody roots in Hungarian folk music using self-organizing maps with adaptively weighted dynamic time warping. Applied Artificial Intelligence, 21(1), 35–55.
  • Koduri, G.K., Gulati, S., Rao, P., & Serra, X. (2012). Rāga recognition based on pitch distribution methods. Journal of New Music Research, 41(4), 337–350.
  • Krishna, T.M., & Ishwar, V. (2012). Carnatic music: Svara, gamaka, motif and raga identity. In Proceedings of the 2nd CompMusic Workshop, Istanbul, Turkey, July. Barcelona: Universitat Pompeu Fabra.
  • Lartilott, O., & Ayari, M. (2008). Segmenting Arabic modal improvisation:Comparing listeners’ responses with computer predictions. In Proceedings of the 4th Conference on Interdisciplinary Musicology, Thessaloniki, Greece, July.
  • Music in Motion. (2013). Retrieved June 3, 2013, form http://autrimncpa.wordpress.com/.
  • Pandey, G., Mishra, C., & Ipe, P. (2003). Tansen: A system for automatic raga identification. In Proceedings of the Indian International Conference on Artificial Intelligence, Hyderabad, India, (pp. 1350–1363).
  • Powers, H.S., & Widdess, R. (2001). India III. Theory and practice of classical music. In S. Sadie (Ed.), The New Grove Dictionary of Music and Musicians. London: Macmillan.
  • Rabiner, L., & Juang, B. (1986). An introduction to hidden Markov models. IEEE Acoustics, Speech and Signal Processing Magazine, 3(1), 4–16.
  • Raja, D. (2005). Hindustani music. New Delhi: DK Printworld.
  • Rao, P., Ross, J.C., & Ganguli, K.K. (2013). Distinguishing raga-specific intonation of phrases with audio analysis. Journal of the ITC Sangeet Research Academy, 26–27, 58–69.
  • Rao, S., Bor, J., van der Meer, W., & Harvey, J. (1999). The Raga Guide: A Survey of 74 Hindustani Ragas (Audio CD). Wyastone Leys, UK: Nimbus Records with Rotterdam Conservatory of Music.
  • Rao, S., & Rao, P. (2013). An overview of Hindustani music in the context of computational musicology, in press.
  • Rao, V., & Rao, P. (2010). Vocal melody extraction in the presence of pitched accompaniment in polyphonic music. IEEE Transactions on Audio, Speech, and Language Processing, 18(8), 2145–2154.
  • Ross, J.C., Vinutha, T.P., & Rao, P. (2012). Detecting melodic motifs from audio for Hindustani classical music. In Proceedings of the Conference of the International Society for Music Information Retrieval Conference, Porto, Portugal, October.
  • Sakoe, H., & Chiba, S. (1978). Dynamic programming algorithm optimization for spoken word recognition. IEEE Transactions on Acoustics, Speech and Signal Processing, 26(1), 43–49.
  • Salamon, J., & Gómez, E. (2012). Melody extraction from polyphonic music signals using pitch contour characteristics. IEEE Transactions on Audio, Speech, and Language Processing, 20(6), 1759–1770.
  • Salamon, J., Gulati, S., & Serra, X. (2012). A multipitch approach to tonic identification in Indian classical music. In Proceedings of the 13th international conference on music information retrieval (ISMIR) (pp. 499–504).
  • Subramanian, S.K., Wyse, L., & McGee, K. (2011). Modeling speed doubling in Carnatic music. In Proceedings of International Computer Music Conference (ICMC) (pp. 478–485).
  • van Kranenburg, P., Volk, A., Wiering, F., & Veltkamp, R. C. (2009). Musical models for folk-song melody alignment. In Proceedings of the international conference on music information retrieval (ISMIR) (pp. 507–512).
  • Widdess, R. (1994). Involving the performers in transcription and analysis: A collaborative approach to dhrupad. Ethnomusicology, 38(1), 59–79.
  • Zhu, Y., & Shasha, D. (2003). Warping indexes with envelope transforms for query by humming. In Proceedings of the 2003 ACM SIGMOD International Conference on Management of Data, San Diega, CA, June (pp. 181–192). New York: ACM.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.