Research Interests

- Content - based Music Retrieval
- Melody Spotting
- Automatic Music Segmentation and Audio Thumbnailing
- Instrument Identififcation
- Repeated Pattern Finding
- Music Genre Classification
- Rhythm and beat detection
- Locating voice segments within music signals
- Hidden Markov Models
- Signal Processing

 

 

 

 

Bibliography

 

Content Based Music Retrieval

  1. Jonathan T. Foote, "Content-Based Retrieval of Music and Audio." In C.-C. J. Kuo et al., editor, Multimedia Storage and Archiving Systems II, Proc. of SPIE, Vol. 3229, pp. 138-147, 1997
  2. J. T. Foote, "An Overview of Audio Information Retrieval." In ACM-Springer Multimedia Systems, vol. 7 no. 1, pp. 2-11, ACM Press/Springer-Verlag, January 1999
  3. Guodong Guo and Stan Z. Li, "Content-Based Audio Classification and Retrieval by Support Vector Machines", IEEE TRANSACTIONS ON NEURAL NETWORKS, VOL. 14, NO. 1, JANUARY 2003
  4. Stan Z. Li, "Content-Based Audio Classification and Retrieval Using the Nearest Feature Line Method", IEEE TRANSACTIONS ON SPEECH AND AUDIO PROCESSING, VOL. 8, NO. 5, SEPTEMBER 2000
  5. Erling Wold, Thorn Blum, Douglas Keislar, and James Wheaton Muscle Fish, "Content-Based Classification, Search, and Retrieval of Audio", IEEE TRANSACTIONS ON MULTIMEDIA, 1996
  6. Kjell Lemstrom,Pauli Laine, "MUSICAL INFORMATION RETRIEVAL USING MUSICAL PARAMETERS", International Computer Music Conference, Ann Arbour, 1998.
  7. Guojun Lu and Templar Hankinson, "A Technique towards Automatic Audio Classification and Retrieval", ICASP 1998

Melody Spotting

  1. A. Pikrakis, S. Theodoridis, D. Kamarotos, "Recognition of Isolated Musical Patterns using Context Dependent Dynamic Time Warping", IEEE Trans. on Speech and Audio Processing, Vol. 11, pp. 175-184, 2003
  2. A. Pikrakis, S. Theodoridis, D. Kamarotos "Recognition of isolated musical patterns using Discrete Observation Hidden Markov Models", EUSIPCO-98, Rhodes, Greece.
  3. A. Pikrakis, S. Theodoridis, D. Kamarotos "Recognition of isolated musical patterns in the context of Greek traditional music using Dynamic Time Warping Techniques", International Computer Music Conference 1997, Thessaloniki, Greece, Sept. 1997.
  4. Durey, Adriane, "Melody Spotting Using Hidden Markov Models ", 2nd Annual International Symposium on Music Information Retrieval 2001
  5. Masataka Goto, Satoru Hayamizu, "A Real-time Music Scene Description System: Detecting Melody and Bass Lines in Audio Signals", Working Notes of the IJCAI-99 Workshop on Computational Auditory Scene Analysis, pp.31-40, August 1999.

 

Automatic Music Segmentation and Audio Thumbnailing

  1. Christopher Raphael, "Automatic Segmentation of Acoustic Musical Signals Using Hidden Markov Models", IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, VOL. 21, NO. 4, APRIL 1999
  2. George Tzanetakis, Perry Cook, "MULTIFEATURE AUDIO SEGMENTATION FOR BROWSING AND ANNOTATION", Proc. 1999 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, New Paltz, New York, Oct. 17-20, 1999
  3. S. Lefevre, B. Maillard, N. Vincent, "A Two Level Classifier Process for Audio Segmentation", IAPR International Conference on Pattern Recognition. Quebec City (Canada). p. 891–894. Aout 2002.
  4. Massimo Melucci Nicola Orio, "Evaluating Automatic Melody Segmentation aimed at Music Information Retrieval", in proceedings JCDL 2002: 310-311
  5. Matthew Cooper, and Jonathan Foote, "Summarizing Popular Music via Structural Similarity Analysis," in Proc. IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA 2003
  6. J. Foote, "Automatic Audio Segmentation using a Measure of Audio Novelty." In Proceedings of IEEE International Conference on Multimedia and Expo, vol. I, pp. 452-455, 2000.
  7. Matt Cooper and Jonathan Foote, "Automatic Music Summarization via Similarity Analysis," in Proc. Third International Symposium on Musical Information Retrieval (ISMIR), pp. 81-85 September 2002, Paris.
  8. Lie Lu, Stan Z. Li and Hong-Jiang Zhang, "CONTENT-BASED AUDIO SEGMENTATION USING SUPPORT VECTOR MACHINES", ACM Multimedia Systems Journal 8 (6), pp. 482-492, March, 2003.

Instrument identification

  1. Tetsuro Kitahara, Masataka Goto, Hiroshi G. Okuno, "Pitch-dependent Musical Instrument Identification and Its Application to Musical Sound Ontology", Proc. of the 16th Int'l Conf. on Industrial & Engineering Applications of Artificial Intelligence and Expert Systems
  2. Tetsuro Kitahara, Masataka Goto, Hiroshi G. Okuno, "Musical Instrument Identification based on F0-dependent Multivariate Normal Distributio", Proc. of the 2003 IEEE Int'l Conf. on Acoustic, Speech and Signal Processing
  3. Tetsuro Kitahara, Masataka Goto, Hiroshi G. Okuno, "Hierarchical Clustering of Musical Instrument Sounds based on Acoustical Similarity", Proc. of the 65th National Convention of IPSJ, 1P-1, Mar.
  4. Tetsuro Kitahara, Masataka Goto, Hiroshi G. Okuno, "Musical Instrument Identification Considering Pitch-dependent Characteristics of Timbre Space ", Proc. of the 2002 Autumn Meeting of the Acoustical Society of Japan, 1-1-4, pp.643-644, Sept. 2002.
  5. Tetsuro Kitahara, Masataka Goto, Hiroshi G. Okuno, "Musical Instrument Identification: A Classifier Considering Pitch-dependent Characteristics of Timbre", IPSJ SIG notes, Music and Computer, 2002-MUS-46-1, Vol.2002, No.63, pp.1-8, July 2002.
  6. Tetsuro Kitahara, Masataka Goto, Hiroshi G. Okuno, "Musical Instrument Identification Considering Pitch-dependent Characteristics of Timbre", IPSJ SIG notes, Music and Computer, 2001-MUS-40-2, Vol.2001, No.45, pp.7-14, May 2001.
  7. Tetsuro Kitahara, Masataka Goto, Hiroshi G. Okuno, "Percussive Instrument Identification using Unsupervised Clustering and Recognition Error Patterns", Proc. of the 65th National Convention of IPSJ, 1P-3, Mar. 2003.
  8. Mark Williams, Ian Kaminskyj, "WEB Based Automatic Classification of Musical Instrument Sounds", ACMC 2002
  9. Slim Essid, Gael Richard, and Bertrand David, "Efficient musical instrument recognition on solo performance music using basic features", AES 25TH INTERNATIONAL CONFERENCE, LONDON, UNITED KINGDOM, 2004 JUNE 17–19
  10. Antti Eronen "AUTOMATIC MUSICAL INSTRUMENT RECOGNITION", Master of Science Thesis, TAMPERE UNIVERSITY OF TECHNOLOGY, Department of Information Technology
  11. Judith C. Brown, Olivier Houix and Stephen McAdams, "Feature dependence in the automatic identification of musical woodwind instruments", J. Acoust. Soc. Am. 109 (3), March 2001
  12. Brown, J.C. "Computer identification of musical instruments using pattern recognition with cepstral coefficients as features." Journal of the Acoustical Society of America Vol. 105, No. 3 (March 1999): 1933-1941.
  13. Brown, J.C. ``Computer Identification of Wind Instruments using Cepstral Coefficients'' Proceedings of the 16th International Congress on Acoustics and 135th Meeting of the Acoustical Society of America, Seattle, Washington, 1889-1890, 1998.
  14. J. Eggink and G. J. Brown (2003) Application of missing feature theory to the recognition of musical instruments in polyphonic audio. Accepted for publication in the Proceedings of the 4th International Conference on Music Information Retrieval (ISMIR-2003), Washington, D.C., 26th-30th October.
  15. Livshin, A., Rodet, X. 2004. "Instrument Recognition Beyond Separate Notes - Indexing Continues Recordings", Presented at ICMC 2004.

 

Repeated Pattern Finding

  1. J.-L. Hsu, C.-C. Liu, and A. L. P. Chen, "Discovering Nontrivial Repeating Patterns in Music Data,'' IEEE Transactions on Multimedia, vol. 3, no. 3, pp. 311-325, 2001.
  2. C.C. Liu, J. L. Hsu and A. L. P. Chen, "Efficient theme and non-trivial repeating pattern discovering in music database", Proc. IEEE International Conference on Data Engineering. 1999.
  3. L. Hsu, C. C. Liu and A. L. P. Chen, “Efficient repeating pattern finding in music databases,” Proc. ACM Seventh International Conference on Information and Knowledge Management (CIKM). 1998.
  4. Pierre-Yves Rolland, "Discovering Patterns in Musical Sequences". Journal of New Music Research, 28 (1999), No. 4, pp. 334-350
  5. Hsuan-Huei Shih, Shrikanth S. Narayanan and C.-C. Jay Kuo, "A DICTIONARY APPROACH TO REPETITIVE PATTERN FINDING IN MUSIC", 2001 IEEE International Conference on Multimedia and Expo
  6. Roger B. Dannenberg and Ning Hu, "Discovering Musical Structure in Audio Recordings" in Music and Artificial Intelligence: Second International Conference, ICMAI 2002, Edinburgh, Scotland, UK. Berlin: Springer, 2002. pp. 43-57.
  7. E. Cambouropolos, M. Crochemore, C. S. Iliopoulos, L. Mouchard, Y. J. Pinzon, "Algorithms for Computing Approximate Repetitions in Musical Sequences" ,International Journal of Computer Mathematics, 79(11), 2002, pp. 1135-1148
  8. C. S. Iliopoulos, T. Lecroq, L. Mouchard, Y. J. Pinzon, "Computing Approximate Repetitions in Musical Sequences", Proc. of Prague Stringology Club Workshop (PSCW'00), Prague, Czech Republic, Collaborative Report DC-2000-03, 2000, pp. 49-59
  9. Lartillot, O., "Discovering musical patterns through perceptive heuristics", Proc. International Symposium on Music Information Retrieval, 2003.
  10. Jia-Lien Hsu, Chih-Chin Liu, Member, IEEE, and Arbee L. P. Chen, Member, IEEE, "Discovering Nontrivial Repeating Patterns in Music Data", IEEE TRANSACTIONS ON MULTIMEDIA, VOL. 3, NO. 3, SEPTEMBER 2001
  11. D. Van Steelant, B. De Baets, H. De Meyer, M. Leman, J.-P. Martens, L. Clarisse, M. Lesaffre, "Discovering Structure and Repetition in Musical Audio", in: Proceedings of Eurofuse Workshop, Varenna, Italy, 2002
  12. Smith, L., & Medina, R. (2001). Discovering themes by exact pattern matching. In J. S. Downie and D. Bainbridge (Eds.), Proceedings of the Second Annual International Symposium on Music Information Retrieval: ISMIR 2001. (pp. 31-32).
  13. K. Lemstrom, J. Tarhio: Searching monophonic patterns within polyphonic sources. In: Proc. RIAO '00, Content-Based Multimedia Information Access (Vol. 2), C.I.D., Paris, 2000, 1261–1279.
  14. David Meredith, Kjell Lemström, Geraint Wiggins, "Algorithms for discovering repeated patterns in multidimensional representations of polyphonic music.", Journal of New Music Research, Vol.31, No.4, pp.321-345.
  15. David Meredith, Kjell Lemström, Geraint Wiggins, "A geometric approach to computing repeated patterns in polyphonic music.", Document submitted to UK Patent office, application number GB 0200203.8.
  16. Benoit Meudic, "Musical pattern extraction: from repetition to musical structure", Proceedings of CMMR (Computer Music Modeling and Retrieval)- Montpellier, May 2003
  17. E. Cambouropoulos, T. Crawford, C.S. Iliopoulos, Pattern processing in melodic sequences: challenges, caveats and prospects, in Computers and the Humanities 35 (1) (2001) pp. 9-21 .
  18. Pierre-Yves Rolland and Jean-Gabriel Ganascia, "Pattern Detection and Discovery: The Case of Music Data Mining", Proceedings of Exploratory Workshop, London, UK, September 16-19, 2002.
  19. J. Foote. "ARTHUR: Retrieving Orchestral Music by Long-Term Structure." In Proceedings of the International Symposium on Music Information Retrieval, Plymouth, Massachusetts, Oct 2000.

Music Genre Classification

  1. George Tzanetakis and Perry Cook, "Musical Genre Classification of Audio Signals", IEEE TRANSACTIONS ON SPEECH AND AUDIO PROCESSING, VOL. 10, NO. 5, JULY 2002
  2. Jean-Julien Aucouturier, Francois Pachet , "Representing Musical Genre: A State of Art", Journal of New Music Research, 2002
  3. T. Li and M. Ogihara and Q. Li, “A comparative study oncontent-based music genre classification,” in Proc. ACM SI-GIR ’03, Toronto, Canada, July 2003, pp. 282–289
  4. J.J. Burred and A. Lerch, “A Hierarchical Approach to auto-matic musical genre classification,” in Proc. 6th Int. Conf. onDigital Audio Effects ’03, London, Great Britain, Sept. 2003.

Rhythm and beat tracking

  1. Masataka Goto and Yoichi Muraoka: A Beat Tracking System for Acoustic Signals of Music, ACM Multimedia Proceedings (Second ACM International Conference on Multimedia), pp.365-372, October 1994.
  2. Masataka Goto and Yoichi Muraoka, "Music Understanding At The Beat Level - Real-time Beat Tracking For Audio Signals ", Working Notes of the IJCAI-95 Workshop on Computational Auditory Scene Analysis, pp.68-75, August 1995.
  3. Masoud Alghoniemy, Ahmed H. Tewfik, "Rhythm and Periodicity Detection in Polyphonic Music", IEEE Signal Processing Society 1999 Workshop on Multimedia Signal Processing, September 13-15, 1999, Copenhagen, Denmark
  4. Simon Dixon, "Automatic Extraction of Tempo and Beat From Expressive Performances", Journal of New Music Research 2001, Vol. 30, No. 1, pp. 39–58
  5. Allen and Dannenberg, "Tracking Musical Beats in Real Time'' in 1990 International Computer Music Conference, International Computer Music Association (September 1990), pp. 140-143.
  6. Klapuri. " Musical meter estimation and music transcription ". Paper presented at the Cambridge Music Processing Colloquium, Cambridge University, UK, 2003.
  7. Klapuri, A., Eronen, A., Astola, J., " Analysis of the meter of acoustic musical signals ," IEEE Trans. Speech and Audio Processing, to appear.
  8. Christian Uhle, Juergen Herre, "ESTIMATION OF TEMPO, MICRO TIME AND TIME SIGNATURE FROM PERCUSSIVE MUSIC", Proc. of the 6th Int. Conference on Digital Audio Effects (DAFX-03), London, UK, September 8-11, 2003
  9. S.Dixon, "A lightweight multi-agent musical beat", PRICAI 2000: Proceedings of the Pacific Rim International Conference on Artificial Intelligence, Melbourne, Australia, 2000, pp 778-788.
  10. S. Dixon, "An Empirical Comparison of Tempo Trackers" ,8th Brazilian Symposium on Computer Music, 31 July - 3 August 2001, Fortaleza, Brazil, pp 832-840
  11. S. Dixon, "A Beat Tracking System for Audio Signals", Proceedings of the Conference on Mathematical and Computational Methods in Music,Vienna, Austria, December 1999, pp 101-110.
  12. Goto, M. and Y. Muraoka (1997). Real-time rhythm tracking for drumless audio signals - chord change detection for musical decisions, IJCAI’97 Workshop on CASA, pp. 135-144
  13. Goto, M. and Y. Muraoka (1998). An audio-based real-time beat tracking system and its applications, ICMC’98, pp. 17-20
  14. Cliff, D. (2000) Hang the DJ: Automatic sequencing and seamless mixing of dance-music tracks. HPL Technical Report, Bristol.
  15. J. Foote, and S. Uchihashi, "The Beat Spectrum: A New Approach to Rhythm Analysis," in Proc. International Conference on Multimedia and Expo (ICME) 2001
  16. Masataka Goto, "An Audio-based Real-time Beat Tracking System for Music With or Without Drum-sounds", Journal of New Music Research2001, Vol. 30, No. 2, pp. 159–171
  17. David Rosenthal, Masataka Goto, Yoichi Muraoka, "Rhythm Tracking Using Multiple Hypotheses", ICMC Proceedings 1994
  18. K. Jensen and T. H. Andersen. "Real-time beat estimation using feature extraction.", In Proceedings of the Computer Music Modeling and Retrieval Symposium, Lecture Notes in Computer Science. Springer Verlag, 2003.
  19. K. Jensen and T. H. Andersen, "Beat estimation on the beat.", In Proceedings of the IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA), New York, October 2003.
  20. Eric D. Scheirer, "Tempo and beat analysis of acoustic musical signals", J. Acoust. Soc. Am. 103 (1), January 1998
  21. Stephen Hainsworth, Malcolm Macleod, "BEAT TRACKING WITH PARTICLE FILTERING ALGORITHMS", 2003 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics
  22. Ye Wang, Miikka Vilermo, "A COMPRESSED DOMAIN BEAT DETECTOR USING MP3 AUDIO BITSTREAMS", ACM Multimedia 2001: 194-202

Locating voice segments within music signals

  1. A.L. Berenzweig and D.P.W. Ellis (2001). "Locating Singing Voice Segments within Music Signals", Proc. IEEE Workshop on Apps. of Sig. Proc. to Acous. and Audio, Mohonk NY, October 2001. (4pp)
  2. T. Zhang, “System and method for automatic singer identification,” HP Labs Technical Report, Dec. 2002.
  3. G.J. Brown and M. Cooke, “Computational auditory scene analysis,” Computer Speech and Language, vol.8, no.2, pp.297-336, 1994.
  4. Chih-Chin Liu, Chuan-Sung Huang, “A singer identification technique for content-based classification of MP3 music objects”, Conference on Information and Knowledge Management, Proceedings of the eleventh international conference on Information and knowledge management
  5. B. Whitman, G. Flake, and S. Lawrence, “Artist detection in music with Minnowmatch,” presented at IEEE Workshop on Neural Networks for Signal Processing, Falmouth, MA, 2001.
  6. E. D. Scheirer and M. Slaney, “Construction and evaluation of a robust multifeature speech/music discriminator,” presented at IEEE Conference on Acoustics, Speech, and Signal Processing (ICASSP), Munich, Germany, 1997.
  7. Kim, Y. E. & Whitman, B. (2002). "Singer identification in popular music recordings using voice coding features." In Proceedings of Interational Conference on Music Information Retrieval (pp. 164–169), Paris, France.
  8. Liu, C. C. & Huang, C. S. (2002). "A singer identification technique for content-based classification of MP3 music objects.", In Proceedings of International Conference on Information and Knowledge Management (pp. 438–445), McLean, Virginia.
  9. Reynolds, D. A. & Rose, R. C. (1995). "Robust text-independent speaker identification using Gaussian mixture speaker models.", IEEE Transactions on Speech and Audio Processing, 3(1), 72?83.
  10. C. K. Wang, R. Y. Lyu, and Y. C. Chiang, “An automatic singing transcription system with multilingual singing lyric recognizer and robust melody tracker,” Proc. Euro. Conf. Speech Communication and Technology (Eurospeech), 2003.
  11. W. H. Tsai, and H. M. Wang, “Automatic singer recognition of popular music recordings via estimation and modeling of solo vocal signal,” submitted to IEEE Transactions on Speech and Audio Processing.
  12. W. H. Tsai, and H. M. Wang, “Towards automatic identification of singing language in popular music recordings,” to appear in Proc. International Conference on Music Information Retrieval, 2004.
  13. Wu Chou and Liang Gu, "Robust Singing Detection in Speech/Music Discriminator Design," International Conference on Acoustics, Speech, and Signal Processing, 2001
  14. Mark A. Bartsch, and Gregory H. Wakefield, "Singing Voice Identification Using Spectral Envelope Estimation", IEEE TRANSACTIONS ON SPEECH AND AUDIO PROCESSING, VOL. 12, NO. 2, MARCH 2004

Hidden Markov Models

  1. Rabiner, L. R., ”A tutorial on hidden Markov models and selected applications in speech recognition”, Proceedings of the IEEE, volume 7, number 2, pages 257-286, 1989
  2. J. Picone, "Continuous Speech Recognition Using Hidden Markov Models", IEEE ASSP Magazine, vol. 7, no. 3, pp. 26-41, July 1990.
  3. “Factorial hidden Markov models (1995)” Zoubin Ghahramani, Michael I. Jordan, Proc. Conf. Advances in Neural Information Processing Systems, NIP
  4. M. Ostendorf, V. Digalakis, O. A. Kimball, "From HMMs to Segment Models: A Unified View of Stochastic Modeling for Speech Recognition", IEEE transactions on Speech and Audio Processing, vol.4, no. 5, September 1995