A Research on the Stochastic Model for Spoken Language Understanding

Abstract

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.KeywordsRecognition RateSpeech RecognitionThreshold ProbabilityUnderstanding SystemSpeech RecognizerThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.