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Large vocabulary natural language continuous speech recognition

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14 Author(s)
L. R. Bahl ; IBM T.J. Watson Res. Center, Yorktown Heights, NY, USA ; R. Bakis ; J. Bellegarda ; P. F. Brown
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A description is presented of the authors' current research on automatic speech recognition of continuously read sentences from a naturally-occurring corpus: office correspondence. The recognition system combines features from their current isolated-word recognition system and from their previously developed continuous-speech recognition system. It consists of an acoustic processor, an acoustic channel model, a language model, and a linguistic decoder. Some new features in the recognizer relative to the isolated-word speech recognition system include the use of a fast match to prune rapidly to a manageable number the candidates considered by the detailed match, multiple pronunciations of all function words, and modeling of interphone coarticulatory behavior. The authors recorded training and test data from a set of ten male talkers. The perplexity of the test sentences was found to be 93; none of sentences was part of the data used to generate the language model. Preliminary (speaker-dependent) recognition results on these talkers yielded an average word error rate of 11.0%

Published in:

Acoustics, Speech, and Signal Processing, 1989. ICASSP-89., 1989 International Conference on

Date of Conference:

23-26 May 1989