Irrelevant variability normalization based HMM training using MAP estimation of feature transforms for robust speech recognition

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

Volumn , Issue , 2008, Pages 4717-4720

  Zhu, Donglai ^a   Huo, Qiang ^b  

^a INSTITUTE FOR INFOCOMM RESEARCH   (Singapore)

^b MICROSOFT RESEARCH ASIA   (China)

Author keywords

Feature transformation; Hidden Markov model; MAP estimate; Robust speech recognition

Indexed keywords

ACOUSTICS; MAXIMUM LIKELIHOOD; MAXIMUM LIKELIHOOD ESTIMATION; PARAMETER ESTIMATION; SIGNAL PROCESSING; SPEECH; SPEECH ANALYSIS;

FEATURE TRANSFORMATION; HIDDEN MARKOV MODEL; INTERNATIONAL CONFERENCES; MAP ESTIMATE; ROBUST SPEECH RECOGNITION;

SPEECH RECOGNITION;

EID: 51449106989     PISSN: 15206149     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICASSP.2008.4518710     Document Type: Conference Paper

References (11)

1. Aurora document AU/217/99, "Availability of Finnish speechdat-car database for ETSI STQ WI008 front-end standardisation," Nokia Nov 1999.
2. ETSI standard document, "Speech processing, transmission and quality aspects (STQ); distributed speech recognition; advanced front-end feature extraction algorithm; compression algorithms," ETSI ES 202 050 v1.1.1 (2002-10), 2002.
3. M. J. F. Gales, "Maximum likelihood linear transformations for HMM-based speech recognition," Computer Speech and Language, vol. 12, pp.75-98, 1998.
4. H. G. Hirsch and D. Pearce, "The AURORA experimental framework for the performance evaluations of speech recognition systems under noisy conditions," ISCA ITRW ASR-2000, Paris, France, 2000, pp.181-188.
5. Q. Huo and D. Zhu, "A maximum likelihood training approach to irrelevant variability compensation based on piecewise linear transformations," Proc. Interspeech 2006 - ICSLP, pp.1129-1132.
6. O. Siohan, T. A. Myrvoll, and C.-H. Lee, "Structural maximum a posteriori linear regression for fast HMM adaptation," Computer, Speech and Language, vol. 16, pp.5-24, 2002.
7. J. Wu and Q. Huo, "An environment compensated minimum classification error training approach based on stochastic vector mapping," IEEE Trans. on Audio, Speech and Language Processing, Vol. 14, No. 6, pp.2147-2155, 2006.
8. J. Wu, Q. Huo, and D. Zhu, "An environment compensated maximum likelihood training approach based on stochastic vector mapping," Proc. ICASSP 2005, pp. 429-432.
9. J. Wu, D. Zhu, and Q. Huo, "A study of minimum classification error training for segmental switching linear Gaussian hidden Markov models," Proc. ICSLP 2004, pp.2813-2816.
10. S. J. Young, et al., The HTK Book (for HTK Version 3.3), 2005.
11. D. Zhu and Q. Huo, "A maximum likelihood approach to unsuper-vised online adaptation of stochastic vector mapping function for robust speech recognition," Proc. ICASSP-2007, pp.IV-773-776.