Dynamic Bayesian Networks for Automatic Speech Recognition

Murat Deviren 1
1 PAROLE - Analysis, perception and recognition of speech
INRIA Lorraine, LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications
Abstract : State-of-the-art automatic speech recognition (ASR) systems are based on probabilistic modelling of the speech signal using Hidden Markov Models. The limitations of these systems under real life conditions arose a question about the robustness of the underlying acoustic modelling methodology. The scope of my thesis is to explore the formalism of Probabilistic Graphical Models, particularly Dynamic Bayesian Networks, from a theoretical and practical point of view, with the aim of developing reliable models of speech and of developing robust ASR systems.
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Conference papers
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https://hal.inria.fr/inria-00100856
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Submitted on : Tuesday, September 26, 2006 - 2:52:29 PM
Last modification on : Thursday, January 11, 2018 - 6:19:55 AM

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Murat Deviren. Dynamic Bayesian Networks for Automatic Speech Recognition. Eighteenth National Conference on Artificial Intelligence, AAAI 2002, SIGART/AAAI Doctoral Consortium, Jul 2002, Edmonton, Alberta, Canada, 1 p. ⟨inria-00100856⟩

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