Towards Very Large Vocabulary Word Recognition
CARNEGIE-MELLON UNIV PITTSBURGH PA DEPT OF COMPUTER SCIENCE
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In this paper, preliminary considerations and some experimental results are presented in an effort to design Very Large Vocabulary Recognition VLVR systems. We will first consider the applicability of current recognition techniques and argue their inadequacy for VLVR. Possible alternate strategies will be explored and their potential usefulness statistically evaluated. Our results indicate that suprasegmental cues such as syllabification, stress patterns, rhythmic patterns, rhythmic patterns and the voiced - unvoiced patterns in the syllables of a word provide powerful mechanisms for search space reduction. Suprasegmental feature could thus operate in a complementary fashion to segmental features.
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