A feature for voice activity detection derived from speech analysis with the exponential autoregressive model

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

Volumn 1, Issue , 2006, Pages

  Ishizuka, Kentaro ^a   Kato, Hiroko ^a  

^a NTT Communication Science Laboratories   (Japan)

Author keywords

[No Author keywords available]

Indexed keywords

AUTOREGRESSIVE MODELS; NOISY SPEECH DATA; NONLINEAR FLUCTUATION; VOCAL CORDS; VOICE ACTIVITY DETECTION;

ACOUSTIC NOISE; ALGORITHMS; CONTROL NONLINEARITIES; FEATURE EXTRACTION; PARAMETER ESTIMATION; SIGNAL ANALYSIS;

SPEECH ANALYSIS;

EID: 33947649580     PISSN: 15206149     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (19)

1. Junqua, J.-C., Mak, B., and Reaves, B. "A robust algorithm for word boundary detection in the presence of noise," IEEE Trans. on Speech and Audio Processing, 2, 406-412, 1994.
2. Srinivasan, K. and Gersho, A. "Voice activity detection for cellular networks," Proc. of IEEE Workshop on Speech Coding for Telecommunications, 85-86, 1993.
3. Le Bouquin-Jeannès R. and Faucon, G. "Study of voice activity detector and its influence on a noise reduction system," Speech Communication, 16, 245-254, 1995.
4. Karray, L. and Martin, A. "Towards improving speech detection robustness for speech recognition in adverse conditions," Speech Communication, 40, 261-276, 2003.
5. Rabiner, L. R. and Sambur, M. R. "An algorithm for determining the endpoints of isolated utterances," The Bell System Technical Journal, 54, 297-315, 1975.
6. Basu, S. "A linked-HMM model for robust voicing and speech detection," Proc. of ICASSP, 1, 816-819, 2003.
7. Kristjansson, T., Deligne, S., and Olsen, P. "Voicing features for robust speech detection," Proc. of Interspeech, 369-372, 2005.
8. Shen, J.-L., Hung, J.-W., and Lee, L.-S. "Robust entropy-based endpoint detection for speech recognition in noisy environments," Proc. of ICSLP, 1998.
9. Tucker, R. "Voice activity detection using a periodicity measure," IEE Proceedings-I, 139, 377-380, 1992.
10. Marzinzik, M. and Kollmeier, B. "Speech pause detection for noise spectrum estimation by tracking power envelope dynamics," IEEE Trans. on Speech and Audio Processing, 10, 109-118, 2002.
11. ITU-T Recommendation G.729, Annex B., 1996.
12. ETSI standard document. ETSI ES 202 050 V1.1.3, 2003.
13. Ishizuka, K., Kato, H., and Nakatani, T. "Speech signal analysis with exponential autoregressive model," Proc. of ICASSP, 1, 225-228, 2005.
14. Aoki, N. and Ifukube, T. "Analysis and perception of spectral 1/f characteristics of amplitude and period fluctuations in normal sustained vowels," J. Acoust. Soc. Am. 106, 423-433, 1999.
15. Haggan, V. and Ozaki, T. "Modelling nonlinear random vibrations using an amplitude-dependent autoregressive time series model," Biometrika, 68, 1, 189-196, 1981.
16. Omura, H. and Tanaka, K. "Speech analysis and synthesis system based on the nonlinear energy damping model," Bulletin of the Electrotechnical Laboratory, 62, 11-21, 1998.
17. Tweedie, R. L. "Sufficient conditions for ergodicity and stationarity of Markov chains on a general state space," Stochastic Process. Appl., 3, 385-403, 1975.
18. Nakamura, A., Matsunaga, S., Shimizu, T., Tonomura, M., and Sagisaka, Y. "Japanese speech databases for robust speech recognition," Proc. of ICSLP, 1998.
19. Merkel, J. D. "The SIFT algorithm for fundamental frequency estimation," IEEE Trans. on Audio and Electroacoustics, AU-20, 367-377, 1972.