Do listeners process noisy speech by taking advantage of “glimpses”—spectrotemporal
regions in which the target signal is least affected by the background? This study used an …

A method is proposed that provides an approximation of the acoustic energy decay (energy–
time curve) in room impulse responses generated using the image-source technique. A …

Under noise-free conditions, the quality of reverberant speech is dependent on two distinct
perceptual components: coloration and long-term reverberation. They correspond to two …

In this study we describe a binaural auditory model for recognition of speech in the presence
of spatially separated noise intrusions, under small-room reverberation conditions. The …

This paper presents an application of missing data techniques in speech enhancement. The
enhancement system consists of two stages: the first stage uses a recurrent neural network …

Looking at practical application scenarios of speech recognition systems several distortion
effects exist that have a major influence on the speech signal and can considerably …

In this study we describe two techniques for handling convolutional distortion withmissing
data'speech recognition using spectral features. The missing data approach to automatic …

A number of studies have explored how speech envelope and temporal fine structure (TFS)
cues contribute to speech perception. Some recent investigations have attempted to process …

In this paper, a robust binaural speech separation system based on deep neural network
(DNN) is introduced. The proposed system has three main processing stages. In the spectral …

Traditionally, automatic speech recognition (ASR) uses a Hidden Markov Model with
Gaussian Mixture Model (HMM-GMM) as acoustic model and hand-designed features such …