References
- IEEE Trans. Signal Processing v.39 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. Speech. Audio Processing v.2 Maximum a posteriori estimation for multivariate Gaussian mixture observations of Markov chains J.-L. Gauvain;C.-H. Lee
- IEEE Trans. Speech. Audio Processing v.3 Bayesian adaptive learning of the parameters of hidden Markov model for speech recognition Q. Huo;C. Chan;C.-H. Lee
- IEEE Trans. Acoust., Speech. Signal Processing v.4 Speaker adaptation using combined transformation and Bayesian methods V. V. Digalakis;L. G. Neumeyer
- Comput. Speech. Language v.9 Maximum likelihood linear regression for speaker adaptation of continuous density hidden Markov models C. J. Leggetter;P. C. Woodland
- Proc. Int. Conf. Spoken Language Processing Vector field smoothing principle for speaker adaptation H. Hattori;S. Sagayama
- Proc. IEEE Int. Conf. Acoust. Speech. Signal Processing A Markov random field approach to Bayesian speaker adaptation B. M. Shahshahani
- Proc. IEEE Int. Conf. Acoust., Speech. Signal Processing Subphonetic modeling with Markov states-senone M.-Y.Hwang;X. Huang
- IEEE Trans. Speech. Audio Processing v.1 Shared-distribution hidden Markov models for speech recognition M.-Y.Hwang;X.Huag
- Optimal statistical decisions M. H. DeGroot
- Proc. IEEE Int. Conf. Acoust. Speech. Signal Processing Implementation of the POW(phonetically optimized words) algorithm for speech database Y. Lim;Y. Lee
- Proc. IEEE Int. Conf. Acoust., Speech. Signal Processing RASTA-PLP speech analysis technique H. Hermansky;N. Morgan;A. Bayya;P. Kohn
- IEEE Trans. Speech. Audio Processing v.5 On-line adptive learning of the continuous density hidden Markov model based on approximate recursive Bayes estimate Q.Huo;C.-H.Lee
- 한국음향회지 v.16 음성학적 지식 기반 변이음 모델을 이용한 가변 어휘 단어 인식기 김희린;이항섭
- J. Acoust. Soc. Korea v.16 no.1E Performance of vacabulary-independent speech recognizers with speaker adaptation O . W. Kwon;C. K. Un.;H. R. Kim.