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Sigmoidal spectral conversion with changeable dynamic region for speech feature extraction

Sigmoidal spectral conversion with changeable dynamic region for speech feature extraction

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© IEE
Published

A noise-resistant feature extraction method for speech recognition in adverse conditions is presented. The proposed method converts the speech spectrum by adjusting the dynamic region of the spectrum based on the level dependent property of auditory nerves. With this method, it is possible to alleviate the problems caused by shrunken spectral dynamic region from heavy background noise.

Inspec keywords: interference suppression; feature extraction; noise; speech recognition

Other keywords: noise-resistant feature extraction method; heavy background noise; auditory nerves; adverse conditions; level dependent property; sigmoidal spectral conversion; speech feature extraction; speech recognition; speech spectrum conversion; changeable dynamic region

Subjects: Speech recognition; Speech recognition and synthesis; Speech processing techniques

References

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      • S.B. Davis , P. Mermelstein . Comparison of parametric representations for monosyllabic word recognitionin continuously spoken sentences. IEEE Trans. Acoust. Speech Signal Process. , 4 , 357 - 366
    2. 2)
      • J.O. Pickles . (1988) An introduction to the physiology of hearing.
    3. 3)
      • J.R. Deller , J.G. Proakis , J.H.L. Hansen . (1993) Discrete-time processing of speech signals.
    4. 4)
      • H. Hermansky , N. Morgan . RASTA processing of speech. IEEE Trans. Speech Audio Process. , 578 - 589
http://iet.metastore.ingenta.com/content/journals/10.1049/el_19990120
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