Dynamic Bayesian Networks for Automatic Speech Recognition - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Conference Papers Year : 2002

Dynamic Bayesian Networks for Automatic Speech Recognition

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.
Not file

Dates and versions

inria-00100856 , version 1 (26-09-2006)

Identifiers

  • HAL Id : inria-00100856 , version 1

Cite

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⟩
54 View
0 Download

Share

Gmail Facebook Twitter LinkedIn More