SEDA: A tunable Q-factor wavelet-based noise reduction algorithm for multi-talker babble

We introduce a new wavelet-based algorithm to enhance the quality of speech corrupted by multi-talker babble noise. The algorithm comprises three stages: The first stage classifies short frames of the noisy speech as speech-dominated or noise-dominated. We design this classifier specifically for mul...

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Bibliographic Details
Published in:Speech communication 2018-02, Vol.96, p.102-115
Main Authors: Soleymani, Roozbeh, Selesnick, Ivan W., Landsberger, David M.
Format: Article
Language:English
Subjects:
Algorithms
Cochlear implants
Components
Denoising
Frames
Intelligibility
Noise
Noise reduction
Speech
Wavelet transforms
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Summary:We introduce a new wavelet-based algorithm to enhance the quality of speech corrupted by multi-talker babble noise. The algorithm comprises three stages: The first stage classifies short frames of the noisy speech as speech-dominated or noise-dominated. We design this classifier specifically for multi-talker babble noise. The second stage performs preliminary de-nosing of noisy speech frames using oversampled wavelet transforms and parallel group thresholding. The final stage performs further denoising by attenuating residual high frequency components in the signal produced by the second stage. A significant improvement in intelligibility and quality was observed in evaluation tests of the algorithm with cochlear implant users.
ISSN:0167-6393
1872-7182
DOI:10.1016/j.specom.2017.11.004