This paper proposes a computationally efficient joint optimization algorithm that performs
online source separation, dereverberation, and noise reduction based on blind and spatially …

Signal separation and extraction are important tasks for devices recording audio signals in
real environments which, aside from the desired sources, often contain several interfering …

This paper addresses the multichannel directional speech enhancement problem with
geometrically constrained independent vector analysis (GCIVA), where we aim to combine …

This paper overviews an appealing unsupervised learning method named independent
vector analysis (IVA) for its promising applications, such as in audio/speech signal …

Dynamic functional connectivity analysis is an effective way to capture the networks that are
functionally associated and continuously changing over the scanning period. However …

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 …

In this paper, we propose an alternative algorithm, which is faster and more stable, for
geometrically constrained independent vector analysis (GC-IVA) to tackle multichannel …

A novel extension of Independent Component and Independent Vector Analysis for blind
extraction/separation of one or several sources from time-varying mixtures is proposed. The …

In many daily-life scenarios, acoustic sources recorded in an enclosure can only be
observed with other interfering sources. Hence, convolutive Blind Source Separation (BSS) …

In this paper, we propose a directional signal extraction network (DSENet). DSENet is a low-
latency, real-time neural network that, given a reverberant mixture of signals captured by a …