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- W100896246 abstract "In this paper, we propose a joint optimal method for automatic speech recognition (ASR) and ideal binary mask (IBM) estimation in transformed into the cepstral domain through a newly derived generalized expectation maximization algorithm. First, cepstral domain missing feature marginalization is established using a linear transformation, after tying the mean and variance of non-existing cepstral coefficients. Second, IBM estimation is formulated using a generalized expectation maximization algorithm directly to optimize the ASR performance. Experimental results show that even in highly non-stationary mismatch condition (dance music as background noise), the proposed method achieves much higher absolute ASR accuracy improvement ranging from 14.69% at 0 dB SNR to 40.10% at 15 dB SNR compared with the conventional noise suppression method." @default.
- W100896246 created "2016-06-24" @default.
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- W100896246 date "2010-09-26" @default.
- W100896246 modified "2023-09-27" @default.
- W100896246 title "Robust automatic speech recognition with decoder oriented ideal binary mask estimation" @default.
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- W100896246 doi "https://doi.org/10.21437/interspeech.2010-583" @default.
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