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ASSP Magazine, IEEE

Issue 3 • Date July 1990

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  • The application of dynamic programming to connected speech recognition

    Page(s): 6 - 25
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    Principles of dynamic programming and its application to discrete-utterance and connected-speech recognition are introduced and discussed. The deterministic form, used for template matching for connected speech, is described in detail, and a number of algorithms are examined. The Viterbi algorithm, which is a form of dynamic programming for a stochastic system, is briefly discussed.<> View full abstract»

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  • Continuous speech recognition using hidden Markov models

    Page(s): 26 - 41
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    The use of hidden Markov models (HMMs) in continuous speech recognition is reviewed. Markov models are presented as a generalization of their predecessor technology, dynamic programming. A unified view is offered in which both linguistic decoding and acoustic matching are integrated into a single, optimal network search framework. Advances in recognition architectures are discussed. The fundamentals of Viterbi beam search, the dominant search algorithm used today in speed recognition, are presented. Approaches to estimating the probabilities associated with an HMM model are examined. The HMM-supervised training paradigm is examined. Several examples of successful HMM-based speech recognition systems are reviewed.<> View full abstract»

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Aims & Scope

This Magazine ceased production in 1990. The current retitled publication is IEEE Signal Processing Magazine.

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