Dynamic Bayesian Networks for Automatic Speech Recognition
Identifieur interne : 008829 ( Main/Merge ); précédent : 008828; suivant : 008830Dynamic Bayesian Networks for Automatic Speech Recognition
Auteurs : Murat DevirenSource :
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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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