Dimension Reduction Method of Speech Feature Vector for Real-Time Adaptation of Voice Activity Detection

음성구간 검출기의 실시간 적응화를 위한 음성 특징벡터의 차원 축소 방법

  • 박진영 (동아대학교 전자공학과) ;
  • 이광석 (진주산업대학교 전자공학과) ;
  • 허강인 (동아대학교 전자공학과)
  • Published : 2006.07.01


In this paper, we propose the dimension reduction method of multi-dimension speech feature vector for real-time adaptation procedure in various noisy environments. This method which reduces dimensions non-linearly to map the likelihood of speech feature vector and noise feature vector. The LRT(Likelihood Ratio Test) is used for classifying speech and non-speech. The results of implementation are similar to multi-dimensional speech feature vector. The results of speech recognition implementation of detected speech data are also similar to multi-dimensional(10-order dimensional MFCC(Mel-Frequency Cepstral Coefficient)) speech feature vector.