Journal of Information Processing Systems

Korea Information Processing Society (한국정보처리학회)
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Thai Classical Music Matching Using t-Distribution on Instantaneous Robust Algorithm for Pitch Tracking Framework

  • Received : 2017.03.22
  • Accepted : 2017.06.17
  • Published : 2017.10.31
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Abstract

The pitch tracking of music has been researched for several decades. Several possible improvements are available for creating a good t-distribution, using the instantaneous robust algorithm for pitch tracking framework to perfectly detect pitch. This article shows how to detect the pitch of music utilizing an improved detection method which applies a statistical method; this approach uses a pitch track, or a sequence of frequency bin numbers. This sequence is used to create an index that offers useful features for comparing similar songs. The pitch frequency spectrum is extracted using a modified instantaneous robust algorithm for pitch tracking (IRAPT) as a base combined with the statistical method. The pitch detection algorithm was implemented, and the percentage of performance matching in Thai classical music was assessed in order to test the accuracy of the algorithm. We used the longest common subsequence to compare the similarities in pitch sequence alignments in the music. The experimental results of this research show that the accuracy of retrieval of Thai classical music using the t-distribution of instantaneous robust algorithm for pitch tracking (t-IRAPT) is 99.01%, and is in the top five ranking, with the shortest query sample being five seconds long.

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References

  1. A. Ghias, J. Logan, D. Chamberlin, and B. C. Smith, "Query by humming: musical information retrieval in an audio database," in Proceedings of the 3rd ACM International Conference on Multimedia, San Francisco, CA, 1995, pp. 231-236.
  2. J. T. Foote, "Content-based retrieval of music and audio," in Proceedings of the Multimedia Storage and Archiving Systems II, Dallas, TX, 1997, pp. 138-147.
  3. C. C. Liu, J. L. Hsu, and A. L. P. Chen, "An approximate string matching algorithm for content-based music data retrieval," in Proceedings of the IEEE International Conference on Multimedia Computing and Systems, Florence, Italy, 1999, pp. 451-456.
  4. Y. E. Kim and B. Whitman, "Singer identification in popular music recordings using voice coding features," in Proceedings of the 3rd International Conference on Music Information Retrieval, Paris, France, 2002, pp. 164-169.
  5. H. M. Yu, W. H. Tsai, and H. M. Wang, "A query-by-singing system for retrieving karaoke music," IEEE Transactions on Multimedia, vol. 10, no. 8, pp. 1626-1637, 2008. https://doi.org/10.1109/TMM.2008.2007345
  6. P. Boonmatham, S. Pongpinigpinyo, and T. Soonklang, "A comparison of audio features of Thai Classical Music Instrument," in Proceedings of the 7th International Conference on Computing and Convergence Technology (ICCCT), Seoul, Korea, 2012, pp. 213-218.
  7. P. Boonmatham, S. Pongpinigpinyo, and T. Soonklang, "Musical-scale characteristics for traditional Thai music genre classification," in Proceedings of the International Computer Science and Engineering Conference (ICSEC), Nakorn Pathom, Thailand, 2013, pp. 227-232.
  8. D. Gusfield, Algorithms on Strings, Trees and Sequences: Computer Science and Computational Biology. Cambridge, UK: Cambridge University Press, 1997.
  9. W. J. Hess, "Pitch and voicing determination of speech with an extension toward music signals," in Springer Handbook of Speech Processing, Berlin, Germany: Springer, 2008, pp. 181-212.
  10. A. Whittall, Serialism. New York, NY: Cambridge University Press, 2008.
  11. D. Talkin, "A robust algorithm for pitch tracking (RAPT)," in Speech Coding and Synthesis, Amsterdam, Netherlands: Elsevier, 1995, pp. 495-518.
  12. E. Azarov, M. Vashkevich, and A. Petrovsky, "Instantaneous pitch estimation based on RAPT framework," in Proceedings of the 20th European Signal Processing Conference (EUSIPCO), Bucharest, Romania, 2012, pp. 2787-2791.
  13. K. Hotta and K. Funaki, "On a robust F0 estimation of speech based on IRAPT using robust TV-CAR analysis," in Proceedings of the Asia-Pacific, Signal and Information Processing Association Annual Summit and Conference (APSIPA), Siem Reap, Cambodia, 2014, pp. 1-4.
  14. L. Jiaxi, "The application and research of T-test in medicine," in Proceedings of the 1st International Conference on Networking and Distributed Computing (ICNDC), Hangzhou, China, 2010, pp. 321-323.
  15. W. G. Cochran, "ES Pearson, John Wishart, "Student's" Collected Papers," The Annals of Mathematical Statistics, vol. 15, no. 4, pp. 435-438, 1944. https://doi.org/10.1214/aoms/1177731216
  16. F. Sha and L. K. Saul, "Real-time pitch determination of one or more voices by nonnegative matrix factorization," in Proceedings of the Advances in Neural Information Processing Systems 17, Vancouver, Canada, 2004, pp. 1233-1240.
  17. N. H. Adams, M. A. Bartsch, and G. H. Wakefield, "Note segmentation and quantization for music information retrieval," IEEE Transactions on Audio, Speech, and Language Processing, vol. 14, no. 1, pp. 131-141, 2006. https://doi.org/10.1109/TSA.2005.854088
  18. M. Zhao, Z. Li, Y. Wang, and Q. Xu, "Longest common sub-sequence computation and retrieve for encrypted character strings," in Proceedings of the 19th International Conference on Network-Based Information Systems (NBiS), Ostrava, Czech Republic, 2016, pp. 496-499.
  19. P. Senin, "Dynamic time warping algorithm review," Collaborative Software Development Laboratory, Technical Report CSDL-08-04, 2008.