We present AdVerb, a novel audio-visual dereverberation framework that uses visual cues
in addition to the reverberant sound to estimate clean audio. Although audio-only …

Reverberation not only degrades the quality of speech for human perception, but also
severely impacts the accuracy of automatic speech recognition. Prior work attempts to …

Deep-leaming based acoustic echo cancellation (AEC) methods have been shown to
outperform the classical techniques. The main drawback of the learning-based AEC is its …

The reverberation time (RT) and the early-to-late reverberation ratio (ELR) are two key
parameters commonly used to characterize acoustic room environments. In contrast to …

Room reverberation poses various deleterious effects on performance of automatic speech
systems. Speaker identification (SID) performance, in particular, degrades rapidly as …

Acoustic Echo Cancellation (AEC) whose aim is to suppress the echo originated from
acoustic coupling between loudspeakers and microphones, plays a key role in voice …

Advances in speech signal analysis facilitate the development of techniques for remote
biomedical voice assessment. However, the performance of these techniques is affected by …

Deep neural network (DNNs) based Automatic Speech Recognition (ASR) systems are
known vulnerable to adversarial attacks that are maliciously implemented by adding small …

We present a noise-robust adaptation control strategy for block-online supervised acoustic
system identification by exploiting a noise dictionary. The proposed algorithm takes …

This paper introduces a new class of nonlinear filters for nonlinear acoustic echo
cancellation (NLAEC) based on Hermite nonlinear filters (HNFs), which is a sub-class of …