Optimal Solution of a Training Problem in Speech Recognition

IEEE Transactions on Acoustics, Speech, and Signal Processing

Volumn 33, Issue 1, 1985, Pages 326-329

  Nádas, Arthur ^a  

^a IBM T J WATSON RESEARCH CENTER   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

OPTIMAL BAYES SOLUTION; PROBABILITY ESTIMATOR;

SPEECH;

EID: 0022012892     PISSN: 00963518     EISSN: None     Source Type: Journal    
DOI: 10.1109/TASSP.1985.1164513     Document Type: Article

References (8)

1. S. Das Gupta, “Optimum rules for classification into two multivariate variate normal populations with the same covariance matrix,” in Handbook of Statistics, vol. 2, Krishnaiah and Kanal, Eds. New York: North Holland, 1982, pp. 47–60.
2. T. S. Ferguson, Mathematical Statistics, A Decision Theoretic Approach. New York: Academic, 1967.
3. S. Geisser, “Bayesian discrimination,” Handbook of Statistics, vol. 2, Krishnaiah and Kanal, Eds. New York: North Holland, 1982, pp. 101–120.
4. F. Jelinek, R. L. Mercer, and L. R. Bahl, “Continuous speech recognition: Statistical methods,” Handbook of Statistics, vol. 2, Krishnaiah and Kanal, Eds. New York: North Holland, 1983, pp. 549–573.
5. A. Nádas, “Hidden Markov chains, the forward-backward algorithm and initial statistics,” IEEE Trans. Acoust., Speech, Signal Processing, vol. ASSP-31, pp. 504–506, 1983.
6. —, “A decision theoretic formulation of a training problem in speech recognition and a comparison of training by unconditional versus conditional maximum likelihood,” IEEE Trans. Acoust., Speech, Signal Processing, vol. ASSP-31, pp. 814–817, 1983.
7. C. R. Rao, “A general theory of discrimination when the information about alternative population distributions is based on samples,” Ann. Math. Statist., vol. 25, pp. 651–670, 1954.
8. S. S. Wilks, Mathematical Statistics. New York: Wiley, 1962.