In this paper, we propose a new stochastic model for sentence speech understanding using dictionary and thesaurus. The proposed model searches the dictionary for the same word with input text. If it is not in the dictionary, the proposed model search the high level words in the high level word dictionary based on the thesaurus. We compare the probability of sentence understanding model with threshold probability, and we'll get 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. © Springer-Verlag 2004.
CITATION STYLE
Roh, Y. W., Hong, K. S., & Lee, H. G. (2004). A research on the stochastic model for spoken language understanding. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 3043, 89–96. https://doi.org/10.1007/978-3-540-24707-4_12
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