AR-GARCH in presence of noise: Parameter estimation and its application to voice activity detection

IEEE Transactions on Audio, Speech and Language Processing

Volumn 19, Issue 4, 2011, Pages 916-926

  Mousazadeh, Saman ^a   Cohen, Israel ^a  

^a TECHNION ISRAEL INSTITUTE OF TECHNOLOGY   (Israel)

Author keywords

Autoregressive generalized autoregressive conditional heteroscedasticity (AR GARCH); noisy data; nonstationary noise; parameter estimation; voice activity detector (VAD)

Indexed keywords

AUTO-REGRESSIVE; CRITICAL ISSUES; GARCH MODELS; GARCH PROCESS; GENERALIZED AUTOREGRESSIVE CONDITIONAL HETEROSCEDASTICITY; LIKELIHOOD FUNCTIONS; LIKELIHOOD RATIOS; LOW SIGNAL-TO-NOISE RATIO; MODEL PARAMETERS; NOISE VARIANCE ESTIMATION; NOISE VARIATIONS; NOISY DATA; NONSTATIONARY NOISE; NOVEL TECHNIQUES; PARAMETER ESTIMATION METHOD; SPEECH SIGNALS; TIME DOMAIN; TIME-VARYING VARIANCE; VOICE ACTIVITY DETECTION; VOICE ACTIVITY DETECTOR (VAD);

COMPUTER SIMULATION; DETECTORS; MAXIMUM LIKELIHOOD ESTIMATION; METAL ANALYSIS; SIGNAL DETECTION; SIGNAL TO NOISE RATIO; SPEECH COMMUNICATION; SPEECH RECOGNITION; TIME DOMAIN ANALYSIS;

PARAMETER ESTIMATION;

EID: 79953283970     PISSN: 15587916     EISSN: None     Source Type: Journal    
DOI: 10.1109/TASL.2010.2070494     Document Type: Article

References (24)

1. N. R. Garner, P. A. Barrett, D. M. Howard, and A. M. Tyrrell, "Robust noise detection for speech detection and enhancement," Electron. Lett., vol. 33, pp. 270-271, Feb. 1997. (Pubitemid 127546321)
2. A. Benyassine, E. Shlomot, H. Su, D. M. C. Lamblin, and J. Petit, "ITU-T recommendation G.729 annex B: A silence compression scheme for use with g.729 optimized for v.70 digital simultaneous voice and data applications," IEEE Commun. Mag., vol. 35, no. 5, pp. 64-73, Sep. 1997. (Pubitemid 127557050)
3. J. Sohn, N. S. Kim, and W. Sung, "A statistical model-based voice activity detection," IEEE Signal Process. Lett., vol. 16, no. 1, pp. 1-3, Jan. 1999.
4. J. Ramirez and J. C. Segura, "Statistical voice activity detection using a multiple observation likelihood ratio test," IEEE Signal Process. Lett., vol. 12, no. 10, pp. 689-692, Oct. 2005. (Pubitemid 41448576)
5. J. H. Chang and N. S. Kim, "Voice activity detection based on complex Laplacian model," Electron. Lett., vol. 39, no. 7, pp. 632-634, Apr. 2003.
6. J. W. Shin, J. H. Chang, H. S. Yun, and N. S. Kim, "Voice activity detection based on generalized gamma distribution," in Proc. IEEE Int. Conf. Acoust., Speech, Signal Process., 2005, vol. 1, pp. I781-I784. (Pubitemid 43761269)
7. A. Davis, S. Nordholm, and R. Togneri, "Statistical voice activity detection using low-variance spectrum estimation and an adaptive threshold," IEEE Trans. Audio, Speech, Lang. Process., vol. 14, no. 2, pp. 412-424, Mar. 2006.
8. I. Cohen, "Speech spectral modeling and enhancement based on autoregressive conditional heteroscedasticity models," Signal Process., vol. 86, pp. 698-709, 2006. (Pubitemid 43242967)
9. Y. Ephraim and D. Malah, "Speech enhancement using a minimum mean-square error short-time spectral amplitude estimator," IEEE Trans. Acoust., Speech, Signal Process., vol. ASSP-32, no. 6, pp. 1109-1121, Dec. 1984.
10. H. Solvang, K. Ishizuka, and M. Fujimoto, "Voice activity detection based on adjustable linear prediction and GARCH models," Speech Commun., vol. 50, pp. 476-486, 2008.
11. S. M. J. Benesty and J. Chen, Speech Enhancement, S. M. J. Benesty and J. Chen, Eds. Berlin, Germany: Springer, 2005.
12. I. Cohen, "Noise spectrum estimation in adverse environments: Improved minima controlled recursive averaging," IEEE Trans. Speech Audio Process., vol. 11, no. 5, pp. 466-475, Sep. 2003.
13. T. Bollerslev, "Generalized autoregressive conditional heteroscedasticity," J. Econometrics, vol. 31, pp. 307-327, 1986.
14. R. Engle, "Autoregressive conditional heteroskedasticity with estimates of the variance of U.K. inflation," Econometrica, vol. 50, pp. 987-1008, 1982.
15. W. Li, S. Ling, and M. McAleer, "Recent theoretical results for time series models with GARCH errors," J. Economic Surveys, vol. 16, pp. 245-269, 2002.
16. J. S. Garofolo, "Getting started with the DARPA TIMIT CD-ROM: An acoustic phonetic continuous speech database," Tech. Rep., Dec. 1988, (prototype as of), National Institute of Standards and Technology (NIST).
17. P. Stoica and R. L. Moses, Introduction to Spectral Analysis, M. Horton, Ed. Englewood Cliffs, NJ: Prentice-Hall, 1997.
18. S. M. Kay, Fundamentals of Statistical Signal Processing: Estimation, A. V. Oppenheim, Ed. Englewood Cliffs: Prentice-Hall Signal Processing Series, 1993.
19. D. G. Luenberger, Linear and Nonlinear Programming. Reading, MA: Addison-Wesley, 1989.
20. S. Mousazadeh and I. Cohen, "Simultaneous parameter estimation and state smoothing of complexGARCHprocess in the presence of additive noise," Signal Process., vol. 90, pp. 2947-2953, Nov. 2010.
21. V. Tadic and A. Doucet, "Exponential forgetting and geometric ergodicity for optimal filtering in general state-space models," Stochast. Process. Their Applicat., vol. 115, pp. 1408-1436, 2005. (Pubitemid 40890105)
22. L. Ljung and T. Söderström, Theory and Practice of Recursive Identification. Cambridge, MA: MIT Press, 1983.
23. P. D. Tuan, "Maximum likelihood estimation of the autoregressive model by relaxation on the reflection coefficients," IEEE Trans. Acoust., Speech, Signal Process., vol. 36, no. 8, pp. 1363-1367, Aug. 1988.
24. S. Gazor and W. Zhang, "A soft voice activity detector based on a Laplacian Gaussian model," IEEE Trans. Speech Audio Process., vol. 11, no. 5, pp. 498-505, Sep. 2003.