A study on robustness of large vocabulary mandarin chinese continuous speech recognition system based on wavelet analysis

  • Authors:

  • Long Yan;Gang Liu;Jun Guo

  • Affiliations:

  • Beijing University of Posts and Telecommunications, Beijing, P.R. China;Beijing University of Posts and Telecommunications, Beijing, P.R. China;Beijing University of Posts and Telecommunications, Beijing, P.R. China

  • Venue:
  • ICAPR'05 Proceedings of the Third international conference on Advances in Pattern Recognition - Volume Part I
  • Year:
  • 2005

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Abstract

In this paper wavelet decomposition is used to decompose speech signal into five levels. Low-frequency part of the speech signal was reconstructed. Because different frequencies of the speech signal have different influence on the performance of the system, the acoustic model of each level was trained and tested. The experimental results show that the acoustic model of level 1 is the best for clean speech and the acoustic model of level 2 is the best for noisy speech .It is proved that the frequency band of A1 makes a lot of contribution on the performance of clean speech and the frequency band of A2 makes a lot of contribution on the performance of noisy speech.