Discriminative training for improved neural prediction systems

Presents improvements to neural predictive systems for acoustic-phonetic decoding. They allow to raise the performances of these systems close to the state of the art. Important increases have been obtained through carefully selected discriminant criteria.<<ETX>>

[1]  Esther Levin Hidden control neural architecture modeling of nonlinear time varying systems and its applications , 1993, IEEE Trans. Neural Networks.

[2]  Hervé Bourlard,et al.  Continuous speech recognition , 1995, IEEE Signal Process. Mag..

[3]  Alex Waibel,et al.  Continuous speech recognition using linked predictive neural networks , 1991, [Proceedings] ICASSP 91: 1991 International Conference on Acoustics, Speech, and Signal Processing.

[4]  Abdelhamid Mellouk,et al.  A discriminative neural prediction system for speech recognition , 1993, 1993 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[5]  Patrick Gallinari,et al.  Continuous Speech Recognition Predictive Systems , 1993 .

[6]  Ken-ichi Iso,et al.  Large vocabulary speech recognition using neural prediction model , 1991, [Proceedings] ICASSP 91: 1991 International Conference on Acoustics, Speech, and Signal Processing.

[7]  P. Gallinari,et al.  A speech recognizer optimally combining learning vector quantization, dynamic programming and multi-layer perceptron , 1992, [Proceedings] ICASSP-92: 1992 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[8]  Neural Predi LARGE VOCABULARY SPEECH RECOGNITION USING NEURAL PREDICTION MODEL , 1991 .

[9]  J. Makhoul,et al.  Linear prediction: A tutorial review , 1975, Proceedings of the IEEE.

[10]  Satoru Hayamizu,et al.  Continuous Speech Recognition Techniques for Protein Structure Prediction Systems , 1992 .