Incorporating mask modelling for noise-robust automatic speech recognition

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

Volumn , Issue , 2009, Pages 3929-3932

  Köküer, Münevver ^a   Jančovič, Peter ^a  

^a UNIVERSITY OF BIRMINGHAM   (United Kingdom)

Author keywords

Automatic speech recognition; Mask modelling; Missing feature theory; Noise robustness

Indexed keywords

AUTOMATIC SPEECH RECOGNITION; EXPERIMENTAL EVALUATION; MISSING-FEATURE THEORY; NOISE ROBUSTNESS; NOISE-ROBUST AUTOMATIC SPEECH RECOGNITION; NOISY SPEECH; PERFORMANCE IMPROVEMENTS; THE STANDARD MODEL; TRAINING PROCEDURES; VITERBI;

ACOUSTIC NOISE; ACOUSTICS; HIDDEN MARKOV MODELS; SIGNAL PROCESSING;

SPEECH RECOGNITION;

EID: 70349210266     PISSN: 15206149     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICASSP.2009.4960487     Document Type: Conference Paper

References (13)

1. S.F. Boll, "Suppression of acoustic noise in speech using spectral subtraction," IEEE Trans. on Acoustic, Speech, and Signal Proc., vol. 27, no. 2, pp. 113-120, Apr. 1979.
2. S.V. Vaseghi, Advanced Digital Signal Processing and Noise Reduction, John Wiley & Sons, 2005.
3. M.J.F. Gales and S.J. Young, "Robust continuous speech recognition using parallel model combination," IEEE Trans. on Speech and Audio Proc., vol. 4, pp. 352-359, 1996.
4. R.P. Lippmann and B.A. Carlson, "Using missing feature theory to actively select features for robust speech recognition with interruptions, filtering and noise," Eurospeech, Rhodes, Greece, pp. 37-40, 1997.
5. M. Cooke, P. Green, L. Josifovski, and A. Vizinho, "Robust automatic speech recognition with missing and unreliable acoustic data," Speech Communication, vol. 34, no. 3, pp. 267-285, 2001.
6. Q. Zhu and A. Alwan, "Non-linear feature extraction for robust speech recognition in stationary and nonstationary noise," Computer Speech and Language, vol. 17, pp. 381-402, 2003.
7. M. Padmanabhan, "Spectral peak tracking and its use in speech recognition," ICSLP, Beijing, China, 2000.
8. G. Farahani, S.M. Ahadi, and M.M. Homayounpoor, "Use of spectral peaks in autocorrelation and group delay domains for robust speech recognition," ICASSP, Toulouse, France, vol. I, pp. 517-520, 2006.
9. C. Huang, Y. Huang, F. Soong, and J. Zhou, "Weighted likelihood ratio (WLR) hidden Markov model for noisy speech recognition," ICASSP, Toulouse, France, vol. I, pp. 37-40, 2006.
10. P. Jaňcovič and M. Köküer, "On the mask modeling and feature representation in the missing-feature ASR: Evaluation on the Consonant Challenge," Interspeech, Brisbane, Australia, pp. 1777-1780, 2008.
11. C. Nadeu, D. Macho, and J. Hernando, "Time and frequency filtering of filter-bank energies for robust HMM speech recognition," Speech Communication, vol. 34, pp. 93-114, 2001.
12. S. Young, D. Kershaw, J. Odell, D. Ollason, V. Valtchev, and P. Woodland, The HTK Book. V2.2, 1999.
13. P. Jančovič and M. Köküer, "Estimation of voicingcharacter of speech spectra based on spectral shape," IEEE Signal Processing Letters, vol. 14, no. 1, pp. 66-69, Jan. 2007.