Acoustic feature compensation based on decomposition of speech and noise for ASR in noisy environments

EUROSPEECH 2001 - SCANDINAVIA - 7th European Conference on Speech Communication and Technology

Volumn , Issue , 2001, Pages 421-424

  Kim, Hong Kook ^a   Rose, Richard C ^a   Kang, Hong Goo ^a  

^a AT AND T LABS RESEARCH   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ACOUSTIC NOISE; ERROR COMPENSATION; MEAN SQUARE ERROR; SPEECH; SPEECH COMMUNICATION; SPEECH ENHANCEMENT;

AUTOMATIC SPEECH RECOGNITION; FEATURE COMPENSATION; MINIMUM MEAN SQUARED ERROR; MISMATCHED CONDITIONS; NOISY SPEECH RECOGNITION; PERFORMANCE COMPARISON; SPECTRAL AMPLITUDE ESTIMATORS; SPEECH ENHANCEMENT ALGORITHM;

SPEECH RECOGNITION;

EID: 85009124851     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (14)

1. Junqua, J.-C. and Haton, J.-P., Robustness in automatic speech recognition, Boston, MA: Kluwer Academic, 1996.
2. Kermorvant, C, A comparison of noise reduction techniques for robust speech recognition, IDIAP Research Report, IDIAP-RR 99-10, July 1999.
3. Gales, M. and Young, S. J., "Robust continuous speech recognition using parallel model combination, " IEEE Trans. Speech Audio Process., vol. 4, no. 5, pp. 352-359, Sept. 1996.
4. Ephraim, Y. and Malah, D., "Speech enhancement using a minimum mean-square error log-spectral amplitude estimator, " IEEE Trans. ASSP, vol. 33, no. 2, pp. 443-445, Apr. 1985.
5. Malah, D., Cox, R. V., and Accardi, A. J., "Tracking speech- presence uncertainty to improve speech enhancement in non- stationary noise environments" in Proc. ICASSP, Phoenix, AZ, vol. 2, pp. 789-792, Mar. 1999.
6. Accardi, A. J. and Cox, R. V., "A modular approach to speech enhancement with an application to speech coding" in Proc. ICASSP, Phoenix, AZ, vol. 1, pp. 201-204, Mar. 1999.
7. Pearce, D. and Hirsch, H., "The AURORA experimental framework for the performance evaluation of speech recognition systems under noisy conditions, " in Proc. ICSLP, Beijing, China, Oct. 2000.
8. Martin, R., "Spectral subtraction based on minimum statistics, " in Proc. Euro. Signal Process. Conf. (EUSIPCO), Edinburgh, UK, pp. 1182-1185, Sept. 1994.
9. Martin, R. and Cox, R. V., "New speech enhancement techniques for low bit rate speech coding, " in Proc. 1999 IEEE Workshop on Speech Coding, Porvoo, Finland, pp. 165-167, June 1999.
10. Chengalvarayan, R., "Look-A-head sequential feature vector normalization for noisy speech recognition, " in Proc. ICSLP, Beijing, China, Oct. 2000.
11. Leonard, R. G., "A database for speaker-independent digit recognition, " in Proc. ICASSP, San Diego, CA, vol. 3, pp. 42.11.1-4, Mar. 1984.
12. Rahim, M., et al., "Signal conditioning techniques for robust speech recognition, " IEEE Signal Process. Lett., vol. 3, no. 4, pp. 107-109, Apr. 1996.
13. Sharp, R. D., et al., "The WATSON speech recognition engine, " in Proc. ICASSP, Munich, German, pp. 4065-4068, Apr. 1997.
14. ETSI ES 201 108 v1.1.2, Speech processing, transmission and quality aspects (STQ); Distributed speech recognition; front-end feature extraction algorithm; compression algorithms, Apr. 2000.