No Yong Wan , Hong Gwang Seog

The KIPS Transactions:PartB , Vol. 10, No. 7, pp. 829-836, Dec. 2003
10.3745/KIPSTB.2003.10.7.829,   PDF Download:

Abstract

In this paper, we propose a stochastic model for sentence speech understanding using dictionary and thesaurus. The proposed model extracts words from an input speech or text into a sentence. A computer is sellected category of dictionary database compared the word extracting from the input sentence calculating a probability value to the compare results from stochastic model. At this time, computer read out upper dictionary information from the upper dictionary searching and extracting word compared input sentence caluclating value to the compare results from stochastic model. We compare adding the first and second probability value from the dictionary searching and the upper dictionary searching with threshold probability that we measure the sentence understanding rate. We evaluated the performance of the sentence speech understanding system by applying twenty questions game. As the experiment results, we got sentence speech understanding accuracy of 79.8%. In this case, probability(α) of high level word is 0.9 and threshold probability(β) is 0.38.

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