Titlebook: Connectionist Speech Recognition; A Hybrid Approach Hervé A. Bourlard,Nelson Morgan Book 1994 Springer Science+Business Media New York 1994

Somber

Coherent Structures in Turbulence,ability that a particular acoustic vector is emitted at a given time only depends on the current state and the current acoustic vector. As a consequence, this model does not take account of the dynamic nature of the speech signal..

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Hidden Markov Modelsical method of estimating the probabilistic functions of Markov chains.’ Shortly afterwards, they were extended to automatic speech recognition independently at CMU [Baker, 1975b] and IBM [Bakis, 1976; Jelinek, 1976].

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System Tradeoffse also has consequences for training. A particular design choice implies some tradeoff between these requirements. Additionally, trained systems such as those considered here may require entirely different resources for training and recognition modes, and these will be traded off in different techniques.

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Statistical Pattern Classificationcontext of a long history of pattern recognition technology. Though specific methods are changing, the pattern recognition perspective continues to be useful for the description of many problems and their proposed solutions.

SUE

Hidden Markov Modelsn modeling the lexicon words or the constituent speech units by Hidden Markov Models (HMMs) [Baker 1975a,; Jelinek 1976; Bahl et al.,1983; Levinson et al., 1983; Rabiner & Juang, 1986]. First described in [Baum & Petrie, 1966; Baum & Eagon, 1967; Baum, 1972], this formalism was proposed as a statist

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