Speech feature extraction method using subband-based periodicity and nonperiodicity decomposition

Journal of the Acoustical Society of America

Volumn 120, Issue 1, 2006, Pages 443-452

  Ishizuka, Kentaro ^a   Nakatani, Tomohiro ^a   Minami, Yasuhiro ^a   Miyazaki, Noboru ^b  

^a NTT Corporation   (Japan)

^b NTT CORPORATION   (Japan)

Author keywords

[No Author keywords available]

Indexed keywords

ACOUSTIC NOISE; DECOMPOSITION; SENSORY PERCEPTION; SPEECH PROCESSING; SPEECH RECOGNITION; SPEECH SYNTHESIS;

AUDITORY COMB FILTERING; NOISE SPECTRUM; PARALLEL DISTRIBUTED PROCESSING; SPEECH PERCEPTION;

FEATURE EXTRACTION;

ARTICLE; HUMAN; HUMAN EXPERIMENT; MATHEMATICAL MODEL; NOISE REDUCTION; NORMAL HUMAN; PERIODICITY; PRIORITY JOURNAL; PSYCHOPHYSICS; SIGNAL NOISE RATIO; SPEECH DISCRIMINATION; SPEECH PERCEPTION;

ALGORITHMS; FEMALE; HUMANS; MALE; MODELS, BIOLOGICAL; NORMAL DISTRIBUTION; PERIODICITY; PSYCHOACOUSTICS; SPEECH; SPEECH PERCEPTION; SPEECH PRODUCTION MEASUREMENT; TIME FACTORS;

EID: 33745738849     PISSN: 00014966     EISSN: None     Source Type: Journal    
DOI: 10.1121/1.2205131     Document Type: Article

References (48)

1. Aikawa, K., Singer, H., Kawahara, H., and Tohkura, Y. (1996). "Cepstral representation of speech motivated by time-frequency masking: An application to speech recognition," J. Acoust. Soc. Am. 100, 603-614.
2. Ali, A. M., Spiegel, J. V., and Mueller, P. (2002). "Robust auditory-based speech processing using the average localized synchrony detection," IEEE Trans. Speech Audio Process. 10, 279-292.
3. Atal, B. S. (1974). "Effectiveness of linear prediction characteristics of the speech wave for automatic speaker identification and verification," J. Acoust. Soc. Am. 55, 1304-1312.
4. Bernard, A., Gong, Y., and Cui, X. (2004). "Can back-ends be more robust than front-ends? Investigation over the Aurora-2 database," Proc. of the 29th International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Vol. 1, pp. 1025-1028.
5. Bogert, B., Healy, M., and Tukey, J. (1963). "The quefrency analysis of time series for echoes," in Proc. Symp. on Time Series Analysis, edited by M. Rosenblatt (Wiley, New York), pp. 209-243.
6. Boll, S. (1979). "Suppression of acoustic noise in speech using spectral subtraction," IEEE Trans. Acoust., Speech, Signal Process. ASSP-27, 113-210.
7. Darwin, C. J., and Carlyon, R.P. (1995). "Auditory grouping," in Hearing, edited by B. C. J. Moore (Academic, San Diego), pp. 387-424.
8. Davis, S. B., and Mermelstein, P. (1980). "Comparison of parametric representations for monosyllabic word recognition in continuously spoken sentences," IEEE Trans. Acoust., Speech, Signal Process. ASSP-28, 357-366.
9. de Cheveigné, A. (1993). "Separation of concurrent harmonic sounds: Fundamental frequency estimation and a time-domain cancellation model of auditory processing," J. Acoust. Soc. Am. 93, 3271-3290.
10. de Cheveigné, A. (1997). "Concurrent vowel identification. III. A neural model of harmonic interference cancellation," J. Acoust. Soc. Am. 101, 2857-2865.
11. de Veth, J., Cranen, B., and Boves, L. (2001). "Acoustic features and distance measure to reduce vulnerability of ASR performance due to the presence of a communication channel and/or background noise," in Robustness in Language and Speech Technology, edited by J.-C. Junqua and G. van Noord (Kluwer Academic, Dordrecht, Netherlands), pp. 9-45.
12. Gales, M., and Young, S. (1993). "HMM recognition in noise using parallel model combination," Proc. of the 3rd European Conference on Speech Communication and Technology (Eurospeech), pp. 837-840.
13. Gao, Y., Huang, T., Chen, S., and Haton, J.-P. (1992). "Auditory model based speech processing," Proc. of the 2nd International Conference on Spoken Language Processing (ICSLP), pp. 73-76.
14. Ghitza, O. (1988). "Temporal non-place information in the auditory nerve firing patterns as a front-end for speech recognition in a noisy environment," J. Phonetics 16, 109-124.
15. Ghitza, O. (1994). "Auditory models and human performance in tasks related to speech coding and speech recognition," IEEE Trans. Speech Audio Process. 2, 115-132.
16. Gong, Y. (1995). "Speech recognition in noisy environments: A survey," Speech Commun. 16, 261-291.
17. Greenberg, S. (2004). "Speech processing in the auditory system: An overview," in Speech Processing in the Auditory System, edited by S. Greenberg, W. A. Ainsworth, A. N. Popper, and R. R. Fay (Springer-Verlag, New York).
18. Hermansky, H. (1990). "Perceptual Linear Predictive (PLP) analysis of speech," J. Acoust. Soc. Am. 87, 1738-1752.
19. Hermansky, H., Hanson, B., and Wakita, H. (1985). "Low-dimensional representation of vowels based on all-pole modeling in the psychophysical domain," Speech Commun. 4, 181-187.
20. Hess, W. (1983). "Short-term analysis pitch determination," in Pitch Determination of Speech Signals (Springer-Verlag, New York).
21. Hirsh, H. G., and Pearce, D. (2000). "The AURORA experimental framework for the performance evaluation of speech recognition systems under noisy conditions," Proc. of the ISCA Tutorial and Research Workshop on Automatic Speech Recognition (ISCA ITRW ASR), pp. 181-188.
22. Huang, X., Acero, A., and Hon, H. (2001). "Speech signal representation," in Spoken Language Processing (Prentice-Hall, Englewood Cliffs, NJ).
23. Ishizuka, K., and Aikawa, K. (2002). "Effect of F0 fluctuation and amplitude modulation of natural vowels on vowel identification in noisy environments," Proc. of the 7th International Conference on Spoken Language Processing (ICSLP), pp. 1633-1636.
24. Itakura, F. (1975). "Minimum prediction residual principle applied to speech recognition," IEEE Trans. Acoust., Speech, Signal Process. ASSP-23, 67-72.
25. Jackson, P. J. B., and Shadle, C. H. (2001). "Pitch-scaled estimation of simultaneous voiced and turbulence-noise components in speech," IEEE Trans. Speech Audio Process. 9, 713-726.
26. Jackson, P. J. B., Moreno, D. M., Russell, M. J., and Hernando, J. (2003). "Covariation and weighting of harmonically decomposed streams for ASR," Proc. of 8th European Conference on Speech Communication and Technology (Eurospeech), pp. 2321-2324.
27. Johnson, D. H. (1980). "The relationship between spike rate and synchrony in responses of auditory-nerve fibers to single tones," J. Acoust. Soc. Am. 68, 1115-1122.
28. Kajita, S., and Itakura, F. (1995). "Robust feature extraction using SBCOR analysis," Proc. of the 20th International Conference on Acoustics, Speech, and Signal Processing (ICASSP), pp. 421-424.
29. Kim, D. S., Lee, S. Y., and Kil, R. M. (1999). "Auditory processing of speech signals for robust speech recognition in real-world noisy environments," IEEE Trans. Speech Audio Process. 7, 55-69.
30. Koo, B., Gibson, J., and Gray, S. (1989). "Filtering of colored noise for speech enhancement and coding," Proc. of the 14th International Conference on Acoustics, Speech, and Signal Processing (ICASSP), pp. 349-352.
31. Lee, C.-H., Lin, C.-H., and Juang, B.-H. (1991). "A study on speaker adaptation of the parameters of continuous density hidden Markov models," IEEE Trans. Signal Process. 39, 806-814.
32. Li, Q., Soong, F. K., and Siohan, O. (2001). "An auditory system-based feature for robust speech recognition," Proc. of the 7th European Conference on Speech Communication and Technology (Eurospeech), pp. 619-621.
33. Lim, J., and Oppenheim, A. (1978). "All-pole modeling of degraded speech," IEEE Trans. Acoust., Speech, Signal Process. ASSP-26, 197-210.
34. Lockwood, P., and Boudy, J. (1992). "Experiments with a Nonlinear Spectral Subtractor (NSS), hidden Markov models and the projection, for robust speech recognition in cars," Speech Commun. 11, 215-228.
35. Minami, Y., and Furui, S. (1995). "A maximum likelihood procedure for a universal adaptation method," Proc. of the 20th International Conference on Acoustics, Speech, and Signal Processing (ICASSP), pp. 129-132.
36. Moore, B. C. J., and Glasberg, B. R. (1983). "Suggested formula for calculating auditory-filter bandwidths and excitation patterns," J. Acoust. Soc. Am. 74, 750-753.
37. Nakamura, S., Yamamoto, K., Takeda, K., Kuroiwa, S., Kitaoka, N., Yamada, T., Mizumachi, M., Nishiura, T., Fujimoto, M., Saso, A., and Endo, T. (2003). "Data collection and evaluation of AURORA-2 Japanese corpus," Proc. of the 8th IEEE Workshop on Automatic Speech Recognition and Understanding (ASRU), pp. 619-623.
38. Nakamura, S., Takeda, K., Yamamoto, K., Yamada, T., Kuroiwa, S., Kitaoka, N., Nishiura, T., Sasou, A., Mizumachi, M., Miyajima, C., Fujimoto, M., and Endo, T. (2005). "AURORA-2J: An evaluation framework for Japanese noisy speech recognition," IEICE Trans. Inf. Syst. E88-D, 535-544.
39. Patterson, R. D. (1976). "Auditory filter shapes derived with noise stimuli," J. Acoust. Soc. Am. 59, 640-654.
40. Patterson, R. D., and Moore, B. C. J. (1986). "Auditory filters and excitation patterns as representations of frequency resolution," in Frequency Selectivity in Hearing, edited by B. C. J. Moore (Academic, London), pp. 123-177.
41. Pearce, D., and Hirsh, H. G. (2000). "The AURORA experimental framework for the performance evaluation of speech recognition systems under noise conditions," Proc. of the 6th International Conference on Spoken Language Processing (ICSLP), Vol. 4, pp. 29-32.
42. Rabiner, L. R. (1977). "On the use of autocorrelation analysis for pitch detection," IEEE Trans. Acoust., Speech, Signal Process. 25, 24-33.
43. Rose, J. E., Hind, J. E., Anderson, D. J., and Brugge, J. F. (1971). "Some effects of the stimulus intensity on response of auditory nerve fibers in the squirrel monkey," J. Neurophysiol. 34, 685-699.
44. Seneff, S. (1988). "A joint synchrony/mean-rate model of auditory speech processing," J. Phonetics 16, 55-76.
45. Sim, B. L., Tong, Y. C., Chang, J. S., and Tan, C. T. (1998). "A parametric formulation of the generalized spectral subtraction method," IEEE Trans. Speech Audio Process. 6, 328-337.
46. Singh, R., Stern, R. M., and Raj, B. (2002). "Signal and feature compensation methods for robust speech recognition," in Noise Reduction in Speech Applications, edited by G. M. Davis (CRC, Boca Raton, FL), pp. 219-244.
47. Varga, A., and Moore, R. (1990). "Hidden Markov model decomposition of speech and noise," Proc. of the 15th International Conference on Acoustic, Speech and Signal Processing (ICASSP), pp. 845-848.
48. Vaseghi, S., and Milner, B. (1993). "Noisy speech recognition based on HMMs, Wiener filters and re-evaluation of most likely candidates," Proc. of the 18th International Conference on Acoustics, Speech, and Signal Processing (ICASSP), pp. 437-440.