Robust Noise Estimation Applied to Different Speech Estimators

نویسندگان

  • Markus Schwab
  • Hyoung-Gook Kim
  • Peter Noll
چکیده

In this paper we present a robust noise estimation for speech enhancement algorithms. The robust noise estimation based on a modified minima controlled recursive averaging noise estimator was applied to different speech estimators. The investigated speech estimators were spectral substraction (SS), log spectral amplitude speech estimator (LSA) and optimally modified log spectral amplitude estimator (OM-LSA). The performance of the different algorithms were measured both by the signal-tonoise ratio (SNR) and recognition accuracy of an Automatic Speech Recognition (ASR).

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تاریخ انتشار 2003