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- W844977603 abstract "본 논문에서는 사전과 시소러스를 이용하여 문장음성 이해를 위한 확률모델을 제안한다. 제안한 확률모델은 입력되는 음성과 텍스트 문장에서 단어를 추출한다. 컴퓨터가 선택한 카테고리의 사전 DB와 입력된 문장에서 추출된 단어와 비교하고 확률모델로부터 확률값을 얻는다. 이때 컴퓨터로부터 상위어 정보를 알아내고 상위어 사전을 검색하여 단어를 추출하고 입력된 단어와 확률 모델을 비교하여 결과값을 얻는다. 사전과 상위어 사전으로부터 얻은 두개의 확률값을 더하고 그 값을 미리 정해진 임계값과 비교하여 문장의 이해도를 측정한다. 이와 같은 이해 시스템을 스무고개 게임에 적용시켜 그 성능을 평가 하였다. 상위어 확률 값(<TEX>$alpha$</TEX>)이 0.9이고 임계값 (<TEX>$beta$</TEX>)은 0.38일 때 문장음성 이해의 정확도는 79.8%였다. 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 (<TEX>$alpha$</TEX>) of high level word is 0.9 and threshold probability (<TEX>$beta$</TEX>) is 0.38." @default.
- W844977603 created "2016-06-24" @default.
- W844977603 date "2003-12-01" @default.
- W844977603 modified "2023-09-26" @default.
- W844977603 title "A study on the Stochastic Model for Sentence Speech Understanding" @default.
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- W844977603 doi "https://doi.org/10.3745/kipstb.2003.10b.7.829" @default.
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