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Publications (3)
We introduce a real-time capable algorithm which estimates the long-term signal to noise ratio (SNR) of the speech in multi-talker babble noise. In real-time applications, long-term SNR is calculated over a sufficiently long moving frame of the noisy speech ending at the current time. The algorithm performs the real-time long-term SNR estimation by...
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...
Evaluating a New Algorithm for Multi-Talker Babble Noise Reduction Using Resonance Based Signal Decomposition.
Roozbeh Soleymani, Ivan W. Selesnick, David M. Landsberger
Background: One of the key challenges for cochlear implant (CI) users is understanding speech in background noise. Previously, many different single-channel noise reduction algor...