Speech reinforcement in noisy reverberant environments using a perceptual distortion measure

In this paper, a time-frequency weighting is proposed for speech reinforcement (near-end listening enhancement) in a noisy and reverberant environment, which optimizes a perceptual distortion measure locally for each time-frequency bin. The algorithm acts as a dynamic range compressor, smearing out the energy of the clean speech along time. Simulations predict an intelligibility increase with respect to the unprocessed condition and two reference methods, for moderate smoothing windows, as measured by the optimized distortion measure and two objective intelligibility measures.