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Exploiting Contextual Information for Improved Phoneme Recognition
Type of publication: Conference paper
Citation: pinto:icassp-phnrecog:2008
Booktitle: "IEEE Int. Conf. on Acoustics, Speech, and Signal Processing (ICASSP)"
Year: 2008
Note: IDIAP-RR 07-65
Crossref: pinto:rr07-65:
Abstract: In this paper, we investigate the significance of contextual information in a phoneme recognition system using the hidden Markov model - artificial neural network paradigm. Contextual information is probed at the feature level as well as at the output of the multilayerd perceptron. At the feature level, we analyse and compare different methods to model sub-phonemic classes. To exploit the contextual information at the output of the multilayered perceptron, we propose the hierarchical estimation of phoneme posterior probabilities. The best phoneme (excluding silence) recognition accuracy of 73.4\% on the TIMIT database is comparable to that of the state-of-the-art systems, but more emphasis is on analysis of the contextual information.
Userfields: ipdmembership={speech},
Projects Idiap
Authors Pinto, Joel Praveen
Hermansky, Hynek
Yegnanarayana, B.
Magimai.-Doss, Mathew
Added by: [UNK]
Total mark: 0
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