Implementation of A Fast Preprocessor for Isolated Word Recognition

고립단어 인식을 위한 빠른 전처리기의 구현

  • 안영목 (한국전자통신연구소 음성언연구실)
  • Published : 1997.02.01

Abstract

This paper proposes a very fast preprocessor for isolated word recognition. The proposed preprocessor has a small computational cost for extracting candidate words. In the preprocessor, we used a feature sorting algorithm instead of vector quantization to reduce the computational cost. In order to show the effectiveness of our preprocessor, we compared it to a speech recognition system based on semi-continuous hidden Markov Model and a VQ-based preprocessor by computing their recognition performances of a speaker independent isolated word recognition. For the experiments, we used the speech database consisting of 244 words which were uttered by 40 male speakers. The set of speech data uttered by 20 male speakers was used for training, and the other set for testing. As the results, the accuracy of the proposed preprocessor was 99.9% with 90% reduction rate for the speech database.

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