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Discriminative model combination is a new approach in the field of automatic speech recognition. It aims at an optimal integration of all given (acoustic and language) models into one log-linear posterior probability distribution. As opposed to the maximum entropy approach, the coefficients of the log-linear combination are estimated on training samples using discriminative methods to obtain an optimal classifier.
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Peter Beyerlein (2002) studied this question.
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