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The Speech Recognition Based on the Bark Wavelet Front-End Processing

  • Xueying Zhang
  • Zhiping Jiao
  • Zhefeng Zhao
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3614)

Abstract

The paper uses Bark wavelet filter instead of the FIR filter as front-end processor of speech recognition system. Bark wavelet divides frequency band based on critical band and its bandwidths are equal in Bark domain. By selecting suitable parameters, Bark wavelet can overcome the disadvantage of dyadic wavelet and M-band wavelet dividing frequency band based on octave. The paper gave the concept and parameter setting method of Bark wavelet. For signals that are filtered by Bark wavelet, ZCPA features with noise-robust are extracted and used in speech recognition. And recognition network uses HMM. The results show the recognition rates of the system in noise environments are improved.

Keywords

Recognition Rate Speech Recognition Shanxi Province Speech Data Linear Frequency 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 1.
    Kim, D.S., Lee, S.Y., Rhee, M.K.: Auditory processing of speech signal for robust speech recognition in real-world noisy environments. IEEE Transactions on Speech and Audio Processing 7(1), 55–68 (1999)CrossRefGoogle Scholar
  2. 2.
    Fu, Q., Yi, K.C.: Bark wavelet transform of speech and its application in speech recognition. Journal of Electronics 28(10), 102–105 (2000)Google Scholar
  3. 3.
    Gajic, B., Kudldip, K.P.: Robust speech recognition using feature based on zero-crossings with peak amplitudes. In: ICASSP, vol. 1, pp. 64–67 (2003)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Xueying Zhang
    • 1
  • Zhiping Jiao
    • 1
  • Zhefeng Zhao
    • 1
  1. 1.College of Information EngineeringTaiyuan University of TechnologyTaiyuanP.R. China

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