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

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The Hybrid HMM/MLP Approachf the speech signal. However, notwithstanding their efficiency, standard HMM-based recognizers suffer from several weaknesses, mainly due to the many hypotheses required to make their optimization possible (see Chapter 3):

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Fluid Mechanics and Its Applicationsn 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

Awning

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Analytical Theories and Stochastic Models, performance currently achieved by state of the art systems is not yet at the level of a mature technology. Over the years, many technological innovations have boosted the level of performance for more and more difficult tasks. Some of the most significant of these innovations include: (1) pattern m

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,Towards “Real World Turbulence”,f the speech signal. However, notwithstanding their efficiency, standard HMM-based recognizers suffer from several weaknesses, mainly due to the many hypotheses required to make their optimization possible (see Chapter 3):