Study of Noise Robust Voice Activity Detection Based on Periodic Component to Aperiodic Component Ratio

ITRW on Statistical and Perceptual Audio Processing, SAPA 2006

Volumn , Issue , 2006, Pages 65-70

  Ishizuka, Kentaro ^a   Nakatani, Tomohiro ^a  

^a NTT Communication Science Laboratories   (Japan)

Author keywords

[No Author keywords available]

Indexed keywords

ACOUSTIC NOISE; AUDITION; SPEECH RECOGNITION;

APERIODIC COMPONENTS; APRIORI; ENVIRONMENTAL SOUNDS; NOISE ROBUST; NON-STATIONARITIES; PERIODIC COMPONENTS; REAL-WORLD; SOUND CHANGE; VOICE ACTIVITY DETECTION ALGORITHMS; VOICE-ACTIVITY DETECTIONS;

SIGNAL TO NOISE RATIO;

EID: 85133167678     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (26)

1. 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.
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. Junqua, J.-C., Mak, B., and Reaves, B. “A robust algorithm for word boundary detection in the presence of noise,” IEEE Trans. Speech Audio Process., 2, 406-412, 1994.
4. Karray, L. and Martin, A. “Towards improving speech detection robustness for speech recognition in adverse conditions,” Speech Communication, 40, 261-276, 2003.
5. Marzinzik, M. and Kollmeier, B. “Speech pause detection for noise spectrum estimation by tracking power envelope dynamics,” IEEE Trans. Speech Audio Process., 10, 109-118, 2002.
6. Sohn, J., Kim, N.-S., and Sung, W. “A statistical model-based voice activity detection,” IEEE Signal Process. Lett., 6, 1-3, 1999.
7. Basu, S. “A linked-HMM model for robust voicing and speech detection,” Proc. ICASSP, 1, 816-819, 2003.
8. Rabiner, L. R. and Sambur, M. R. “An algorithm for determining the endpoints of isolated utterances,” The Bell Syst. Tech. Journal, 54, 297-315, 1975.
9. Atal, B. S. and Rabiner, L. R. “A pattern recognition approach to voiced-unvoiced-silence classification with applications to speech recognition,” IEEE Trans. Acoust., Speech, and Signal Process., ASSP-24, 201-212, 1976.
10. Kingsbury, B., Saon, G., Mangu, L., Padmanabhan, M., and Sarikaya, R. “Robust speech recognition in noisy environments: The 2001 IBM SPINE evaluation system,” Proc. ICASSP, 1, 53-56, 2002.
11. Kristjansson, T., Deligne, S., and Olsen, P. “Voicing features for robust speech detection,” Proc. Interspeech, 369-372, 2005.
12. Shen, J.-L., Hung, J.-W., and Lee, L.-S. “Robust entropy-based endpoint detection for speech recognition in noisy environments,” Proc. ICSLP, 1998.
13. Yantorno, R. E., Krishnamachari, K. L., and Lovekin, J. M. “The spectral autocorrelation peak valley ratio (SAPVR) - A usable speech measure employed as a co-channel detection system,” Proc. IEEE Int. Workshop Intell. Signal Process., 2001.
14. Tucker, R. “Voice activity detection using a periodicity measure,” IEE Proceedings-I, 139, 377-380, 1992.
15. ITU-T Recommendation G.729 Annex B., 1996.
16. ETSI standard document, ETSI ES 202 050 V1.1.3., 2003.
17. Li, K., Swamy, N. S., and Ahmad, M. O. “An improved voice activity detection using higher order statistics,” IEEE Trans. Speech Audio Process., 13, 965-974, 2005.
18. Lee, A., Nakamura, K., Nisimura, R., Saruwatari, H., and Shikano K. “Noise robust real world spoken dialogue system using GMM based rejection of unintended inputs,” Proc. Interspeech, 1, 173-176, 2004.
19. de Cheveigné, A. “Separation of concurrent harmonic sounds: Fundamental frequency estimation and a time-domain cancellation model of auditory processing,” J. Acoust. Soc. Am., 93, 3271-3290, 1993.
20. Serra, X. and Smith, J. “Spectral modeling and synthesis: A sound analysis/synthesis system based on a deterministic plus stochastic decomposition,” Comp. Music J., 14, 1990.
21. Yegnanarayana, B., d'Alessandro, C., and Darsinos, V. “An iterative algorithm for decomposition of speech signals into periodic and aperiodic components,” IEEE Trans. Speech Audio Process., 6, 1-11, 1998.
22. Richard, G. and d'Alessandro, C. “Modification of the aperiodic component of speech signals for synthesis,” in Progress in Speech Synthesis, van Santen, J. P. H., Sproat, R. W., Olive, J. P., and Hirschberg, J. Eds. New-York: Springer-Verlag, 41-56, 1996.
23. Jackson, P. J. B., Moreno, D. M., Russell, M. J. and Hernando, J. “Covariation and weighting of harmonically decomposed streams for ASR,” Proc. Interspeech, 2321-2324, 2003.
24. Ishizuka, K., Nakatani, T., Minami, Y., and Miyazaki, N. “Speech feature extraction method using subband-based periodicity and nonperiodicity decomposition,” J. Acoust. Soc. Am., 120, 443-452, 2006.
25. Nakatani, T. and Irino, T., “Robust and accurate fundamental frequency estimation based on dominant harmonic components,” J. Acoust. Soc. Am., 116, 3690-3700, 2004.
26. 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. “AURORA-2J: An evaluation framework for Japanese noisy speech recognition,” IEICE Trans. on Inf. & Syst., E88-D, 535-544, 2005.