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Traditional noise-suppression algorithms have been shown to improve speech quality, but not speech intelligibility. Motivated by prior intelligibility studies of speech synthesized using the ideal binary mask, an algorithm is proposed that decomposes the input signal into time-frequency (T-F) units and makes binary decisions, based on a Bayesian classifier,(More)
Existing speech enhancement algorithms can improve speech quality but not speech intelligibility, and the reasons for that are unclear. In the present paper, we present a theoretical framework that can be used to analyze potential factors that can influence the intelligibility of processed speech. More specifically, this framework focuses on the fine-grain(More)
Most noise-reduction algorithms used in hearing aids apply a gain to the noisy envelopes to reduce noise interference. The present study assesses the impact of two types of speech distortion introduced by noise-suppressive gain functions: amplification distortion occurring when the amplitude of the target signal is over-estimated, and attenuation distortion(More)
—While most speech enhancement algorithms improve speech quality, they may not improve speech intelligibility in noise. This paper focuses on the development of an algorithm that can be optimized for a specific acoustic environment and improve speech intelligibility. The proposed method decomposes the input signal into time–frequency (T-F) units and makes(More)
While most speech enhancement algorithms improve speech quality, they do not improve speech intelligibility in noise. The reasons for that remain unclear. In this paper, we present a theoretical framework that can be used to analyze potential factors influencing the intelligibility of processed speech. It is hypothesized that if distortions are properly(More)
—A new binary mask is introduced for improving speech intelligibility based on magnitude spectrum constraints. The proposed binary mask is designed to retain time-frequency (T-F) units of the mixture signal satisfying a magnitude constraint while discarding T-F units violating the constraint. Motivated by prior intelligibility studies of speech synthesized(More)
It has been shown that large gains in speech intelligibility can be obtained by using the binary mask approach which retains the time-frequency (T-F) units of the mixture signal that are stronger than the interfering noise (masker) (i.e., SNR>0 dB), and removes the T-F units where the interfering noise dominates. In this paper, we introduce a new binary(More)