This study presents a fast adaptive algorithm for noise estimation in non-stationary environments. To make noise estimation adapt quickly to non-stationary noise environments, a robust entropy-based voice activity detection (VAD) is thus required. It is well-known that the entropy-based measure defined in spectral domain is very insensitive to the changing level of nose. To exploit the specific nature of straight lines existing on speech-only spectrogram, the proposed spectrum entropy measurement improved from spectrum entropy proposed by Shen et al. is further presented and is named band-splitting spectrum entropy (BSE). Consequently, the proposed recursive noise estimator including BSE-based VAD can update noise power spectrum accurately even if the noise-level quickly changes.
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