Statistical Methods for Speech Recognition (Language, Speech, and Communication)

Statistical Methods for Speech Recognition (Language, Speech, and Communication)

Editorial Reviews
Book Description
This book reflects decades of important research on the mathematical foundations of speech recognition. It focuses on underlying statistical techniques such as hidden Markov models, decision trees, the expectation-maximization algorithm, information theoretic goodness criteria, maximum entropy probability estimation, parameter and data clustering, and smoothing of probability distributions. The author's goal is to present these principles clearly in the simplest setting, to show the advantages of self-organization from real data, and to enable the reader to apply the techniques.

About the Author
Frederick Jelinek is Professor of Electrical and Computer Engineering and Director of the Center for Language and Speech Processing at Johns Hopkins University. For over twenty years he led the IBM Continuous Speech Recognition Group.

Statistical Methods for Speech Recognition (Language, Speech, and Communication),Frederick Jelinek,The MIT Press,0262100665,Automatic Speech Recognition,Computer Books: General,Computers,Computers - General Information,Data Processing - General,Linguistics,Natural Language Processing,Statistical methods,Language Arts & Disciplines / Linguistics

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