Speech enhancement and separation are core problems in audio signal processing, with
commercial applications in devices as diverse as mobile phones, conference call systems …

Studying free-standing conversational groups (FCGs) in unstructured social settings (eg,
cocktail party) is gratifying due to the wealth of information available at the group (mining …

This paper addresses the problem of separating audio sources from time-varying
convolutive mixtures. We propose a probabilistic framework based on the local complex …

Variational autoencoders (VAEs) are powerful (deep) generative artificial neural networks.
They have been recently used in several papers for speech and audio processing, in …

In speech communication systems, the microphone signals are degraded by reverberation
and ambient noise. The reverberant speech can be separated into two components, namely …

This paper presents a blind multichannel speech enhancement method that can deal with
the time-varying layout of microphones and sound sources. Since nonnegative tensor …

The problem of blind separation of speech signals in the presence of noise using multiple
microphones is addressed. Blind estimation of the acoustic parameters and the individual …

This paper presents the design and implementation of a two-stage human-voice
enhancement system for a hose-shaped rescue robot. When a microphoneequipped hose …

This review chapter is dedicated to multichannel audio source separation in a real-life
environment. We explore some of the major achievements in the field and discuss some of …

In this paper we present a new statistical model for the power spectral density (PSD) of an
audio signal and its application to multichannel audio source separation (MASS). The …