Popular music is often composed of an accompaniment and a lead component, the latter
typically consisting of vocals. Filtering such mixtures to extract one or both components has …

We present a novel system for the automatic extraction of the main melody from polyphonic
music recordings. Our approach is based on the creation and characterization of pitch …

In this paper we introduce a low-latency monaural source separation framework using a
Convolutional Neural Network (CNN). We use a CNN to estimate time-frequency soft masks …

When designing an audio processing system, the target tasks often influence the choice of a
data representation or transformation. Low-level time-frequency representations such as the …

Gaussian process (GP) models are very popular for machine learning and regression and
they are widely used to account for spatial or temporal relationships between multivariate …

Nonnegative matrix factorization (NMF) has been traditionally considered a promising
approach for audio source separation. While standard NMF is only suited for single-channel …

This paper proposes a system for score‐informed audio source separation for multichannel
orchestral recordings. The orchestral music repertoire relies on the existence of scores …

La séparation de sources sonores consiste à extraire une ou plusieurs sources présentant
un attrait significatif d'un enregistrement contenant plusieurs sources sonores. Ces …

Facing the rapidly growing amount of digital media, the need for an effective data
management is challenging technology. In this context, we approach the problem of …

We present a deep learning based methodology for extracting the singing voice signal from
a musical mixture based on the underlying linguistic content. Our model follows an encoder …