The Journal of the Korea institute of electronic communication sciences (한국전자통신학회논문지)

Korea Institute of Electronic Communication Science (한국전자통신학회)
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A Study on the Redundancy Reduction in Speech Recognition

음성인식에서 중복성의 저감에 대한 연구

  • 이창영 (동서대학교 시스템경영공학과)
  • Received : 2012.04.18
  • Accepted : 2012.06.07
  • Published : 2012.06.30
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Abstract

The characteristic features of speech signal do not vary significantly from frame to frame. Therefore, it is advisable to reduce the redundancy involved in the similar feature vectors. The objective of this paper is to search for the optimal condition of minimum redundancy and maximum relevancy of the speech feature vectors in speech recognition. For this purpose, we realize redundancy reduction by way of a vigilance parameter and investigate the resultant effect on the speaker-independent speech recognition of isolated words by using FVQ/HMM. Experimental results showed that the number of feature vectors might be reduced by 30% without deteriorating the speech recognition accuracy.

음성 신호의 특성은 인접한 프레임에서 크게 변화하지 않는다. 따라서 비슷한 특징벡터들에 내재된 중복성을 줄이는 것이 바람직하다. 본 논문의 목적은 음성인식에 있어서 음성 특징벡터가 최소의 중복성과 최대의 유효한 정보를 갖는 조건을 찾는 것이다. 이를 이하여 우리는 하나의 감시 파라미터를 통하여 중복성 저감을 실현하고, 그 결과가 FVQ/HMM을 사용한 화자독립 음성인식에 미치는 영향을 조사하였다. 실험 결과, 인식률을 저하시키지 않고 특징벡터의 수를 30% 줄일 수 있음을 확인하였다.

Keywords

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