Vibrato-motivated acoustic features for singer identification

ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

Volumn 5, Issue , 2006, Pages

  Li, Haizhou ^a   Nwe, Tin Lay ^a  

^a INSTITUTE FOR INFOCOMM RESEARCH   (Singapore)

Author keywords

[No Author keywords available]

Indexed keywords

BANDPASS FILTERS; DATABASE SYSTEMS; FEATURE EXTRACTION; INFORMATION ANALYSIS; MATHEMATICAL MODELS; NATURAL FREQUENCIES;

ENHANCED VOCAL DETECTION METHOD; SINGER IDENTIFICATION; VIBRATO MOTIVATED ACOUSTIC FEATURES; VOCAL SEGMENTS;

SPEECH ANALYSIS;

EID: 33947681796     PISSN: 15206149     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (21)

1. T. L. Nwe and Y. Wang, "Automatic Detection of Vocal Segments in Popular Songs", Proceedings of 5th International Conference on Music Information Retrieval (ISMIR), pp. 138-145, 2004.
2. N. C. Maddage, C. Xu, M. S. Kankanhalli and X. Shao, "Content-Based Music Structure Analysis with Applications to Music Semantics Understanding", Proceedings of 12th Annual ACM International Conference on Multimedia, 2004.
3. B. Whitman, O. Flake, and S. Lawrence, "Artist Detection in Music with Minnowmatch" IEEE Workshop on Neural Networks for Signal Processing, pp. 559-568, 2001.
4. T. Zhang, "System and Method for Automatic Singer Identification", IEEE International Conference on Multimedia and Expo, 2003.
5. M. A. Bartsch, and G. H. Wakefield, "Singing Voice Identification Using Spectral Envelope Estimation" TEEE Trans. ASSP, vol. 12, pp. 100-109, 2004.
6. N. C. Maddage, C. Xu and Y. Wang, "Singer Identification Based on Vocal and Instrumental Models" Proc. ICPR Conf., pp. 375 - 378, 2004
7. G. H. Wakefield and M. A. Bartsch, "Where's Caruso? Singer Identification by Listener and Machine" Cambridge Music Processing Colloquium, Cambridge, England, 2003.
8. M. Mellody, F. Herseth, and G. H. Wakefield, "Modal Distribution Analysis, Synthesis, and Perception of A Soprano's Sung Vowels" Journal of Voice, vol. 15, pp. 469-482, 2001.
9. J. Sundberg, The Science of Singing Voice, Northern Illinois University Press, 1987.
10. P. Eric, "Measurements of The Vibrato Rate of Ten Singers", JASA, vol. 96, pp. 1979-1984, 1997.
11. I. Waugh, Song Structure. Music Tech Magazine, 2003.
12. T. L. Nwe, S. W. Foo, and L. C. De Silva, "Stress Classification Using Subband Based Features", IEICE Trans. vol. E86-D, no.3, pp. 565-573, 2003.
13. R. A. Sukkar and L. Chin-Hui, "Vocabulary Independent Discriminative Utterance Verification for Non-keyword Rejection in Subword Based Speech Recognition", IEEE Trans. ASSP, vol. 4, pp. 420-429, 1996.
14. R. Timmers, and P. Desain, Vibrato: Questions and Answers from Musicians and Science. Proc. Int. Conf. On Music Perception And Cognition, England, 2000.
15. J. Bretos and J. Sundberg, "Measurements of Vibrato Parameters in Long Sustained Crescendo Notes As Sung by Ten Sopranos", Journal of Voice, vol. 17, pp. 343-352, 2003.
16. L. J. David, Understanding Vibrato: Vocal Principles that Encourage Development, http://www.voiceteacher.com/vibrato.html
17. C. Dromey, N. Carter and A. Hopkin, "Vibrato Rate Adjustment" Journal of Voice, vol. 17, pp. 168-178, 2003.
18. F. A. Everest, The Master Handbook of Acoustics, New York, Mcgraw-Hill, 2001.
19. C. Seashore, Psychology of Music, New York: Mcgraw-Hill; 1938.
20. L. R. Rabiner, and B. H. Juang, Fundamentals of Speech Recognition, Prentice Hall, Englewood Cliffs, N.J, 1993.
21. C. Becchetti, and L. P. Ricotti, Speech Recognition Theory and C++ Implementation. New York: John Wiley & Sons, 1998.