Abstract
In this paper, a filter used for speech enhancement in speech recognition systems is presented. The filter is based on the Mel-warped Wiener filter and model-based compensation for additive noise. The filter coefficients are designed in Mel-spectral energy domain and then transformed to impulse response in time-domain using Mel-warped inverse discrete cosine transform (Mel-IDCT). The enhanced speech signal is finally obtained by applying the impulse response in time-domain. The performance of the proposed filter has been tested using 863 Database under different noise conditions. The result shows that the speech enhanced by the proposed filter has much higher word accuracy in speech recognition systems.
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