Integrating time alignment and neural networks for high performance continuous speech recognition
暂无分享,去创建一个
[1] Peter F. Brown,et al. The acoustic-modeling problem in automatic speech recognition , 1987 .
[2] Hermann Ney,et al. The use of a one-stage dynamic programming algorithm for connected word recognition , 1984 .
[3] George R. Doddington. Phonetically sensitive discriminants for improved speech recognition , 1989, International Conference on Acoustics, Speech, and Signal Processing,.
[4] Geoffrey E. Hinton,et al. Phoneme recognition using time-delay neural networks , 1989, IEEE Trans. Acoust. Speech Signal Process..
[5] Kiyohiro Shikano,et al. Fast back-propagation learning methods for large phonemic neural networks , 1989, EUROSPEECH.
[6] A. Waibel,et al. Connectionist Viterbi training: a new hybrid method for continuous speech recognition , 1990, International Conference on Acoustics, Speech, and Signal Processing.
[7] Ken-ichi Iso,et al. Speaker-independent word recognition using dynamic programming neural networks , 1989, International Conference on Acoustics, Speech, and Signal Processing,.
[8] Raj Reddy,et al. Large-vocabulary speaker-independent continuous speech recognition: the sphinx system , 1988 .
[9] Alex Waibel,et al. Consonant recognition by modular construction of large phonemic time-delay neural networks , 1989, International Conference on Acoustics, Speech, and Signal Processing,.