Speech recognition apparatus which predicts word classes from co

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G10L 900

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active

052673456

ABSTRACT:
A language generator for a speech recognition apparatus scores a word-series hypothesis by combining individual scores for each word in the hypothesis. The hypothesis score for a single word comprises a combination of the estimated conditional probability of occurrence of a first class of words comprising the word being scored, given the occurrence of a context comprising the words in the word-series hypothesis other than the word being scored, and the estimated conditional probability of occurrence of the word being scored given the occurrence of the first class of words, and given the occurrence of the context. An apparatus and method are provided for classifying multiple series of words for the purpose of obtaining useful hypothesis scores in the language generator and speech recognition apparatus.

REFERENCES:
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Bahl, L. R., et al. "A Maximum Likeihood Approach to Continuous Speech Recognition," IEEE Transactions on Pattern Analysis and Machine Intelligence, volume PAMI-5, No. 2, pp. 179-180, Mar. 1983.
Bahl, L. R., et al. "A Tree-Based Statistical Language Model for Natural Language Speech Recognition." IEEE Transactions on Acoustics, Speech, and Signal Processing, vol. 37, No. 7, Jul. 1989, pp. 1001-1008.
Bahl, L. R., et al. "Vector Quantization Procedure For Speech Recognition Systems Using Discrete Parameter Phoneme-Based Markov Word Models." IBM Technical Disclosure Bulletin, vol. 34, No. 7, Dec. 1989, pp. 340 and 341.
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Mays, E., et al. "Context Based Spelling correction." Information Processing & Management, vol. 27, No. 5, 1991, pp. 517-522.

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