Abstract
Virtually all recognition systems, both research and commercial, place severe limits on the vocabulary and syntactic structures a speaker may use. This recognition system is the most advanced in the world in terms of freedom from this constraint—it allows an essentially unrestricted English vocabulary and sentence structure—although it is currently required that each word be followed by a short pause. Many speech recognition systems make little use of syntactic and semantic information. A trigram language model is employed here that examines the statistical likelihood of each vocabulary word's occurrence as a function of the two preceding words. A global context-sensitive parser is also used which accepts, as input, a long sequence of word candidates. (The speaker is not required to pronounce punctuation marks.) Using rules of English syntax, the parser identifies many erroneous candidates and estimates locations to insert punctuation in the output text. The combined parser and trigram model have raised the accuracy of this system to 92% for ten speakers on an 86 000-word vocabulary. [Work supported by NSERC.]
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