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Connectionist Speech Recognition, A Hybrid Approach Book

Connectionist Speech Recognition, A Hybrid Approach
Connectionist Speech Recognition, A Hybrid Approach, Connectionist Speech Recognition: A Hybrid Approach describes the theory and implementation of a method to incorporate neural network approaches into state of the art continuous speech recognition systems based on hidden Markov models (HMMs) to improve th, Connectionist Speech Recognition, A Hybrid Approach has a rating of 3 stars
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Connectionist Speech Recognition, A Hybrid Approach, Connectionist Speech Recognition: A Hybrid Approach describes the theory and implementation of a method to incorporate neural network approaches into state of the art continuous speech recognition systems based on hidden Markov models (HMMs) to improve th, Connectionist Speech Recognition, A Hybrid Approach
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  • Connectionist Speech Recognition, A Hybrid Approach
  • Written by author Herve Bourlard
  • Published by Springer-Verlag New York, LLC, October 1993
  • Connectionist Speech Recognition: A Hybrid Approach describes the theory and implementation of a method to incorporate neural network approaches into state of the art continuous speech recognition systems based on hidden Markov models (HMMs) to improve th
  • Connectionist Speech Recognition: A Hybrid Approach describes the theory and implementation of a method to incorporate neural network approaches into state of the art continuous speech recognition systems based on hidden Markov models (HMMs) to improv
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List of Figures. List of Tables. Notation. Foreword. Preface. I: Background. 1. Introduction. 2. Statistical Pattern Classification. 3. Hidden Markov Models. 4. Multilayer Perceptions. II: Hybrid HMM/MLP Systems. 5. Speech Recognition using ANNs. 6. Statistical Inference in MLPs. 7. The Hybrid HMM/MLP Approach. 8. Experimental Systems. 9. Context-Dependent MPLs. 10. System Tradeoffs. 11. Training Hardware and Software. III: Additional Topics. 12. Cross-Validation in MLP Training. 13. HMM/MLP and Predictive Models. 14. Feature Extraction by MLP. IV: Finale. 15. Final System Overview. 16. Conclusions. Bibliography. Index. Acronyms.


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Connectionist Speech Recognition, A Hybrid Approach, Connectionist Speech Recognition: A Hybrid Approach describes the theory and implementation of a method to incorporate neural network approaches into state of the art continuous speech recognition systems based on hidden Markov models (HMMs) to improve th, Connectionist Speech Recognition, A Hybrid Approach

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Connectionist Speech Recognition, A Hybrid Approach, Connectionist Speech Recognition: A Hybrid Approach describes the theory and implementation of a method to incorporate neural network approaches into state of the art continuous speech recognition systems based on hidden Markov models (HMMs) to improve th, Connectionist Speech Recognition, A Hybrid Approach

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Connectionist Speech Recognition, A Hybrid Approach, Connectionist Speech Recognition: A Hybrid Approach describes the theory and implementation of a method to incorporate neural network approaches into state of the art continuous speech recognition systems based on hidden Markov models (HMMs) to improve th, Connectionist Speech Recognition, A Hybrid Approach

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