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Stereophonic speech recognition in noise using compensated hidden Markov models

Stereophonic speech recognition in noise using compensated hidden Markov models

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A novel procedure is presented for noise compensation in hidden Markov model speech recognisers. The procedure uses two microphone signals and, unlike previous approaches, does not require the noise spectrum to be stationary even in the short term. Results are presented showing that the performance of the compensated system equals or exceeds that obtained using matched training.

References

    1. 1)
      • Lindsey, G., Breen, A., Nevard, S.: `SPAR's archivable actual-word databases', , Internal Report, June 1987.
    2. 2)
      • S.F. Boll . Suppression of acoustic noise in speech using spectral subtraction. IEEE Trans. , 113 - 120
    3. 3)
      • Varga, A.P., Moore, R.K.: `Hidden Markov model decomposition of speech and noise', Proc. ICASSP, 1990, 2, p. 845–848.
    4. 4)
      • S.B. Davis , P. Mermelstein . Comparison of parametric representations for monosyllabic word recognitionin continuously spoken sentences. IEEE Trans. , 357 - 366
    5. 5)
      • M.S. Brandstein , H.F. Silverman . A practical methodology for speech source localization with microphonearrays. Comput. Speech Lang. , 91 - 126
    6. 6)
      • R. Le Bouquin , G. Faucon . Using the coherence function for noise reduction. IEE Proc I , 276 - 280
    7. 7)
      • Varga, A.P., Steeneken, H.J.M., Tomlinson, M., Jones, D.: `The NOISEX-92 study on the effect of additive noise on automatic speechrecognition', , Technical Report, 1992.
    8. 8)
      • M.J.F. Gales , S.J. Young . Cepstral parameter compensation for HMM recognition in noise. Speech Commun. , 231 - 239
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