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- W1543393933 abstract "We propose an online filtering algorithm that aims to alleviate the decrease we see in ASR performance when the speech is corrupted by additive noise. Using an initial estimate of the noise distribution, the algorithm updates the noise model on a frame synchronous basis. Using Polyak averaging we obtain a sequence of robust, frame-synchronous noise model estimates, and a minimum mean square error (MMSE) filter is used to denoise the cepstral coefficients. The algorithm is compared to a batch version which uses several iterations of the EM-algorithm over the complete utterance to estimate the noise model, and it is shown that the performance obtained using the averaging of the noise model is comparable to the batch performance." @default.
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- W1543393933 date "2006-10-11" @default.
- W1543393933 modified "2023-09-23" @default.
- W1543393933 title "Online cepstral filtering using a sequential EM approach with Polyak averaging and feedback" @default.
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- W1543393933 doi "https://doi.org/10.1109/icassp.2005.1415100" @default.
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