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Statistical Methods for Speech Recognition(H) 요약정보 및 구매

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지은이 Jelinek. Frederick
발행년도 1998-01-16
판수 1판
페이지 284
ISBN 9780262100663
도서상태 구매가능
판매가격 70,500원
포인트 0점
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  • 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.

  • The speech recognition problem
    hidden Markov models
    the acoustic model
    basic language modelling
    the Viterbi search
    hypothesis search on a tree and the fast match
    elements of information theory
    the complexity of tasks - the quality of language models; the expectation - maximization algorithm and its consequences; decision trees and tree language models
    phonetics from orthography - spelling-to-base from mappings
    triphones and allophones
    maximum entropy probability estimation and language models
    three applications of maximum entropy estimation to language modelling
    estimation of probabilities from counts and the Back-Off method.

  • 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.

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