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- W2002296182 abstract "A major axis of research at LIMSI is directed at multilingual, speaker-independent, large vocabulary speech dictation. In this paper the LIMSI recognizer which was evaluated in the ARPA NOV93 CSR test is described, and experimental results on the WSJ and BREF corpora under closely matched conditions are reported. For both corpora word recognition experiments were carried out with vocabularies containing up to 20k words. The recognizer makes use of continuous density HMM with Gaussian mixture for acoustic modeling and n-gram statistics estimated on the newspaper texts for language modeling. The recognizer uses a time-synchronous graph-search strategy which is shown to still be viable with a 20k-word vocabulary when used with bigram back-off language models. A second forward pass, which makes use of a word graph generated with the bigram, incorporates a trigram language model. Acoustic modeling uses cepstrum-based features, context-dependent phone models (intra and interword), phone duration models, and sex-dependent models." @default.
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- W2002296182 date "1994-01-01" @default.
- W2002296182 modified "2023-09-25" @default.
- W2002296182 title "The LIMSI continuous speech dictation system" @default.
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