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Conference Papers Year : 2002

Continuous Speech Recognition using Structural Learning of Dynamic Bayesian Networks

Abstract

We present a new continuous automatic speech recognition system where no a priori assumptions on the dependencies between the observed and the hidden speech processes are made. Rather, dependencies are learned form data using the Bayesian networks formalism. This approach guaranties to improve modelling fidelity as compared to HMMs. Furthermore, our approach is technically very attractive because all the computational effort is made in the training phase.
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Dates and versions

inria-00100855 , version 1 (26-09-2006)

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  • HAL Id : inria-00100855 , version 1

Cite

Murat Deviren, Khalid Daoudi. Continuous Speech Recognition using Structural Learning of Dynamic Bayesian Networks. XI European Signal Processing Conference - EUSIPCO 2002, Sep 2002, Toulouse, France, 4 p. ⟨inria-00100855⟩
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