A comparison of hybrid HMM architecture using global discriminating training
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[1] Hervé Bourlard,et al. Connectionist Speech Recognition: A Hybrid Approach , 1993 .
[2] Peter F. Brown,et al. The acoustic-modeling problem in automatic speech recognition , 1987 .
[3] S Sheffield,et al. RECENT IMPROVEMENTS TO THE ABBOT LARGE VOCABULARY CSR SYSTEM , 1995 .
[4] Hsiao-Wuen Hon,et al. Speaker-independent phone recognition using hidden Markov models , 1989, IEEE Trans. Acoust. Speech Signal Process..
[5] Anthony J. Robinson,et al. An application of recurrent nets to phone probability estimation , 1994, IEEE Trans. Neural Networks.
[6] Renato De Mori,et al. High performance connected digit recognition using maximum mutual information estimation , 1991, [Proceedings] ICASSP 91: 1991 International Conference on Acoustics, Speech, and Signal Processing.
[7] Steve J. Young,et al. State clustering in hidden Markov model-based continuous speech recognition , 1994, Comput. Speech Lang..
[8] John S. Bridle,et al. Alpha-nets: A recurrent 'neural' network architecture with a hidden Markov model interpretation , 1990, Speech Commun..
[9] Les T. Niles,et al. TIMIT phoneme recognition using an HMM-derived recurrent neural network , 1991, EUROSPEECH.
[10] Hervé Bourlard,et al. Neural networks for statistical recognition of continuous speech , 1995, Proc. IEEE.
[11] Chin-Hui Lee,et al. Segmental GPD training of HMM based speech recognizer , 1992, [Proceedings] ICASSP-92: 1992 IEEE International Conference on Acoustics, Speech, and Signal Processing.
[12] Günther Ruske,et al. A hybrid RBF-HMM system for continuous speech recognition , 1995, 1995 International Conference on Acoustics, Speech, and Signal Processing.
[13] R. Schwartz,et al. The N-best algorithms: an efficient and exact procedure for finding the N most likely sentence hypotheses , 1990, International Conference on Acoustics, Speech, and Signal Processing.
[14] Yochai Konig,et al. REMAP: recursive estimation and maximization of a posteriori probabilities in connectionist speech recognition , 1994, EUROSPEECH.
[15] G. Ruske,et al. A hybrid RBF-HMM system for continuous speech recognition , 1995 .
[16] Horacio Franco,et al. Context-dependent connectionist probability estimation in a hybrid hidden Markov model-neural net speech recognition system , 1994, Comput. Speech Lang..
[17] Hervé Bourlard,et al. Connectionist probability estimators in HMM speech recognition , 1994, IEEE Trans. Speech Audio Process..
[18] Steve J. Young,et al. MMI training for continuous phoneme recognition on the TIMIT database , 1993, 1993 IEEE International Conference on Acoustics, Speech, and Signal Processing.
[19] Patrick Haffner,et al. Connectionist speech recognition with a global MMI algorithm , 1993, EUROSPEECH.
[20] Renato De Mori,et al. Search and learning strategies for improving hidden Markov models , 1995, Comput. Speech Lang..
[21] Biing-Hwang Juang,et al. Minimum error rate training of inter-word context dependent acoustic model units in speech recognition , 1994, ICSLP.