Real-time detection of seizure activities in epileptic patients is crucial and can help improve
patients' quality of life. Accurate evaluation, pre-surgery assessments, seizure prevention …

Sound source localization and separation from a mixture of sounds are essential functions
for computational auditory scene analysis. The main challenges are designing a unified …

Speech signals recorded by distant microphones are often contaminated with room
reverberation and signals of interfering speakers. This article addresses the problem of joint …

We consider the Gaussian framework for reverberant audio source separation, where the
sources are modeled in the time-frequency domain by their short-term power spectra and …

This paper deals with the problem of the underdetermined blind separation and tracking of
moving sources. In practical situations, sound sources such as human speakers can move …

This paper presents an unsupervised method that trains neural source separation by using
only multichannel mixture signals. Conventional neural separation methods require a lot of …

We consider the task of separating and classifying individual sound sources mixed together.
The main challenge is to achieve robust classification despite residual distortion of the …

One percent of the world's population suffers from epilepsy, a chronic disorder characterized
by the occurrence of spontaneous seizures. About 30 percent of patients remain medically …

Multichannel signal processing using a microphone array provides fundamental functions
for co** with multi-source situations, such as sound source localization and separation …

In this paper, we exploit Bayesian nonparametric microphone array processing (BNP-MAP)
for analyzing the spatiotemporal patterns of the frog chorus. Such analysis in real …