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Estimation of Global Posteriors and Forward-Backward Training of Hybrid HMM/ANN Systems
Type of publication: Inproceedings
Citation: henn97:euro
Booktitle: European Conference on Speech Communication and Technology (EUROSPEECH 97), Rhodes, Greece
Year: 1997
Pages: 1951-1954
URL: http://diuf.unifr.ch/people/he...
Abstract: The results of our research presented in this paper is two-fold. First, an estimation of global posteriors is formalized in the framework of hybrid HMM/ANN systems. It is shown that hybrid HMM/ANN systems, in which the ANN part estimates local posteriors, can be used to modelize global model posteriors. This formalization provides us with a clear theory in which both REMAP and ``classical'' Viterbi trained hybrid systems are unified. Second, a new forward-backward training of hybrid HMM/ANN systems is derived from the previous formulation. Comparisons of performance between Viterbi and forward-backward hybrid systems are presented and discussed.
Keywords: ANN, MLP, Speech Recognition
Authors Hennebert, Jean
Ris, Christophe
Bourlard, Hervé
Renals, Steve
Morgan, Nelson
Added by: []
Total mark: 0
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