Context-Dependent Connectionist Probability Estimation in a Hybrid HMM-Neural Net Speech Recognition
暂无分享,去创建一个
[1] Hervé Bourlard,et al. Continuous speech recognition using multilayer perceptrons with hidden Markov models , 1990, International Conference on Acoustics, Speech, and Signal Processing.
[2] L. R. Rabiner,et al. An introduction to the application of the theory of probabilistic functions of a Markov process to automatic speech recognition , 1983, The Bell System Technical Journal.
[3] Steve Renals,et al. Connectionist probability estimation in the DECIPHER speech recognition system , 1992, [Proceedings] ICASSP-92: 1992 IEEE International Conference on Acoustics, Speech, and Signal Processing.
[4] John Makhoul,et al. Context-dependent modeling for acoustic-phonetic recognition of continuous speech , 1985, ICASSP '85. IEEE International Conference on Acoustics, Speech, and Signal Processing.
[5] Mitch Weintraub,et al. SRI's DECIPHER System , 1989, HLT.
[6] B. Juang,et al. Context-dependent Phonetic Hidden Markov Models for Speaker-independent Continuous Speech Recognition , 2008 .
[7] Jeffrey L. Elman,et al. Interactive processes in speech perception: the TRACE model , 1986 .
[8] Hervé Bourlard,et al. CDNN: a context dependent neural network for continuous speech recognition , 1992, [Proceedings] ICASSP-92: 1992 IEEE International Conference on Acoustics, Speech, and Signal Processing.
[9] A. Waibel,et al. Connectionist Viterbi training: a new hybrid method for continuous speech recognition , 1990, International Conference on Acoustics, Speech, and Signal Processing.
[10] Frederick Jelinek,et al. Interpolated estimation of Markov source parameters from sparse data , 1980 .