1. Baum, L.E. An inequality and associated maximization techniques in statistical estimation for probabilistic functions of Markov processes / L.E. Baum // Inequalities. - 1972. - № 3. - P. 1-8.
2. A maximization technique occurring in the statistical analysis of probabilistic function of Markov chains / L.E. Baum [et al.]// Ann. Math. Stat. - 1970. - № 41. - P. 164-171.
3. Juang, B.-H. Maximum likelihood estimation for multivariate mixture observations of Mar-kov chains / B.-H. Juang, S.E. Levinson, M.M. Sondhi // IEEE Trans. Inform. Theory. - 1993. - № 2. - P. 307-309.
4. Liporace, L.R. Maximum likelihood estimation for multivariate observations of Markov sources / L.R. Liporace // IEEE Trans. Inform. Theory. - 1995. - № 28. - P. 729-734.
5. Gauvain, J.-L. Maximum a posteriori estimation for multivariate Gaussian mixture observa-tions of Markov chains / J.-L. Gauvain, C.-H. Lee // IEEE Trans. Speech Audio Processing. - 1994. - № 2. - P. 291-298.
6. Huo, Q. Bayesian adaptive learning of the parameters of hidden Markov model for speech recog-nition / Q. Huo, C. Chan, C.-H. Lee // IEEE Trans. Speech Audio Processing. - 1992. - № 5. - P. 334-345.
7. Lee, C.-H. A study on speaker adaptation of the parameters of continuous density hidden Markov models / C.-H. Lee, C.-H. Lin, B.-H. Juang // IEEE Trans. Signal Processing. - 1991. - № 39. - P. 806-814.
8. Matsuoka, T. A study of on-line Bayesian adaptation for HMM-based speech recognition / T. Matsuoka, C.-H. Lee // Proc. EUROSPEECH-93. - Berlin, Germany, 1993. - P. 815-818.
9. Huo, Q. On-Line Adaptive Learning of the Continuous Density Hidden Markov Model Based on Approximate Recursive Bayes Estimate / Q. Huo, C.-H. Lee // Speech and Audio Processing. - 1997. - № 5. - P. 161-172.
10. Rylov, A.S. Analiz rechi v raspoznayushchikh sistemakh / A.S. Rylov. - Minsk : Best-print, 2003. - 264 s.
11. Bilmes, J. A Gentle Tutorial of the EM Algorithm and its Application to Parameter Estima-tion for Gaussian Mixture and Hidden Markov Models / J. Bilmes // International Computer Science Institute. - 1998. - № 1. - P. 164-191.
12. The HTK Book (for HTK v. 3.4) / S. Young [et al.]. - Cambridge University Engineering Department, 2006. - 359 p.
13. Krishnamurthy, V. On-line estimation of hidden Markov model parameters based on the Kullback-Leibler information measure / V. Krishnamurthy, J.B. Moore // IEEE Trans. Signal Processing. - 1993. - № 41 (8). - P. 2557-2573.
14. Weinstein, E. Sequential algorithms for parameter estimation based on the Kullback-Leibler information measure / E. Weinstein, M. Feder, A.V. Oppenheim // IEEE Trans. Acoust, Speech, Signal Processing. - 1990. - № 38 (9). - P. 1652-1654.
15. MULTEXT-J. Japanese MULTEXT Prosodic Corpus [Electronic resource]. - Mode of access : http://research.nii.ac.jp/src/en/MULTEXT-J.html. - Date of access : 30.09.2013.
16. Bou-Ghazale, S.E. A Comparative Study of Traditional and Newly Proposed Features for Recognition of Speech Under Stress / S.E. Bou-Ghazale, J.H.L. Hansen // Speech and Audio Processing. - 2000. - № 8. - P. 429-442.
17. K-fold cross-validation. Wikipedia [Electronic resource]. - Mode of access : http://en.wikipedia.org/wiki/Cross-validation_(statistics). - Date of access : 18.08.2014.
Email this article 