Titlebook: Computational Models of Speech Pattern Processing; Keith Ponting Book 1999 Springer-Verlag Berlin Heidelberg 1999 Dialogue systems.Human s

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Quantenchemie auf Workstation-Clustern still have to be enhanced, especially to improve the robustness of recognition in real conditions. Most of present systems are based on stochastic models, especially hidden Markov models (HMMs). In the past few years, a quite large number of projects have been directed toward the development of a n

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半圓鑿

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Fujitsu VP2000 Series Supercomputer,ecognizer performance. Recently, the . (DFE) method has been applied for estimating transformations of the representation space for speech recognizers. In this work, a variant of the DFE method is applied in order to improve the representation space for Continuous Speech Recognition.

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Science, Simulation and Supercomputersment of fast K-NN algorithms allows to reconsider its use in applications with large sample sets. In this outlook, the K-NN decision principle has been assessed on a frame by frame phonetic identification on the TIMIT database. Thereafter, a method to integrate the K-NN pdf estimator in a HMM-based

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GUILT

An Overview of Computing at Los Alamoses have been proposed for resolving this mismatch problem. These approaches can be divided broadly into three classes: model adaptation, channel adaptation and robust features. This paper presents a review and discussion of methods for channel adaptation and their relationship to methods in the othe

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