REDUCED GAUSSIAN MIXTURE MODELS IN A LARGE VOCABULARY CONTINUOUS SPEECH RECOGNIZER

6th European Conference on Speech Communication and Technology, EUROSPEECH 1999

Volumn , Issue , 1999, Pages 1099-1102

  Fischer, V ^a   Ross T ^a  

^a European Speech Research   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

GAUSSIAN DISTRIBUTION; SPEECH COMMUNICATION; SPEECH PROCESSING; VOCABULARY CONTROL;

CONTINUOUS SPEECH; GAUSSIAN MIXTURE MODEL; GAUSSIAN-MIXTURES; GAUSSIANS; LARGE VOCABULARY; LARGE VOCABULARY CONTINUOUS SPEECH RECOGNITION; MIXTURE COMPONENTS; SPEECH RECOGNITION SYSTEMS; SPEECH RECOGNIZER; STATISTICAL REPRESENTATIONS;

CONTINUOUS SPEECH RECOGNITION;

EID: 51449087653     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (9)

1. L. Bahl, S. Balakrishnan-Aiyer, J. Bellegarda, M. Franz, P. Gopalakrishnan, D. Nahamoo, M. Novak, M. Padmanabhan, M. Picheny, and S. Roukos. Performance of the IBM Large Vocabulary Continuous Speech Recognition System on the ARPA Wall Street Journal Task. In Proc. of the IEEE Int. Conference on Acoustics, Speech, and Signal Processing, pages 41-44, Detroit, 1995.
2. L. Bahl, P. Brown, P. de Souza, and P. Mercer. Maximum Mutual Information Estimation of Hidden Markov Model Parameters for Speech Recognition. In Proc. of the IEEE Int. Conference on Acoustics, Speech, and Signal Processing, pages 49-52, Tokyo, 1986.
3. L. Bahl, P. de Souza, P. Gopalakrishnan, D. Nahamoo, and M. Picheny. Context-dependent Vector Quantization for Continuous Speech Recognition. In Proc. of the IEEE Int. Conference on Acoustics, Speech, and Signal Processing, Minneapolis, 1993.
4. S. Chen and P. Gopalakrishnan. Clustering via the Bayesian Information Criterion with Applications to Speech Recognition. In Proc. of the IEEE Int. Conference on Acoustics, Speech, and Signal Processing, pages 645-648, Seattle, 1998.
5. J. Duchateau, K. Demuynck, and D. Van Campernolle. Fast and Accurate Modelling with Semi-Continuous HMMs. Speech Communication, 24(1):5-17, 1998.
6. M. Jardino. Multilingual Stochastic n-Gramm Class Language Models. In Proc. of the IEEE Int. Conf. on Acoustics, Speech, and Signal Processing, Atlanta, N.Y., 1996.
7. F. Jelinek. Statistical Methods for Speech Recognition. The MIT Press, Cambridge, Ma., 1997.
8. Y. Normandin. Optimal Splitting of HMM Gaussian Mixture Components with MMIE Training. In Proc. of the IEEE Int. Conference on Acoustics, Speech, and Signal Processing, pages 449-452, Detroit, 1995.
9. D. Paul. The Lincoln Tied-mixture HMM Continuous Speech Recognizer. In Proc. of the IEEE Int. Conference on Acoustics, Speech, and Signal Processing, pages 329-332, Toronto, 1991.