Speech enhancement and speech separation are two related tasks, whose purpose is to
extract either one or more target speech signals, respectively, from a mixture of sounds …

An undeniable part of a smart city is its use of smart agents. These agents can vary a lot in
sizes, shapes, and functionalities. Embodied artificial intelligence is the field of study that …

In music source separation, the number of sources may vary for each piece and some of the
sources may belong to the same family of instruments, thus sharing timbral characteristics …

Can we perform an end-to-end music source separation with a variable number of sources
using a deep learning model? This paper presents an extension of the Wave-U-Net [1] …

In the physical sciences and engineering domains, music has traditionally been considered
an acoustic phenomenon. From a perceptual viewpoint, music is naturally associated with …

In this paper, we present a new dataset of music performance videos which can be used for
training machine learning methods for multiple tasks such as audio-visual blind source …

We propose a novel informed music source separation paradigm, which can be referred to
as neuro-steered music source separation. More precisely, the source separation process is …

Large-scale pre-trained audio and image models demonstrate an unprecedented degree of
generalization, making them suitable for a wide range of applications. Here, we tackle the …

Music source separation is the task of isolating individual instruments which are mixed in a
musical piece. This task is particularly challenging, and even state-of-the-art models can …

In audio-visual recordings of music performances, visual cues from instrument players
exhibit good temporal correspondence with the audio signals and the music content. These …