The recent surge in the use of Deep Neural Networks (DNNs) has also made its mark in the
field of Audio Enhancement (AE), providing much better quality than the classical methods …

Blind source separation (BSS) methods have received extensive attention over the past two
decades; thanks to its wide applicability in a number of areas such as biomedical …

Acoustic sensing from a multi-rotor drone is heavily degraded by the strong ego-noise
produced by the rotating motors and propellers. To address this problem, we propose a …

We propose an overdetermined source separation and localization method for a set of M
microphones distributed around an unknown number, N<; M, of sources. We reformulate the …

We propose a time difference of arrival (TDOA) estimation framework based on time-
frequency inter-channel phase difference (IPD) to count and localize multiple acoustic …

In this paper, we investigate the sampling rate mismatch problem in distributed microphone
arrays and propose a correlation maximization algorithm to blindly estimate the sampling …

This paper proposes a novel approach to reducing the word error rate (WER) of an
automatic speech recognition (ASR) system in a noisy reverberant room. This research …

In this paper, a multi-microphone noise reduction system based on the generalized sidelobe
canceller (GSC) structure is investigated. The system consists of a fixed beamformer …

In this paper we present a harmonic constrained Multichannel Non-Negative Matrix
Factorization (MNMF) method for the task of blind music source separation. In this model, the …

An apparatus for multichannel signal processing separates signal components from different
acoustic sources by initial izing a separation filter bank with beams in the estimated Source …