International audienceThis paper considers the blind separation of the harmonic and percussive components of multichannel music signals. We model the contribution of each source to all mixture channels in the time-frequency domain via a spatial covariance matrix, which encodes its spatial characteristics, and a scalar spectral variance, which represents its spectral structure. We then exploit the spatial continuity and the different spectral continuity structures of harmonic and percussive components as prior information to derive maximum a posteriori (MAP) estimates of the parameters using the expectation-maximization (EM) algorithm. Experimental results over professional musical mixtures show the effectiveness of the proposed approach
This thesis presents techniques for the modelling of musical signals, with particular regard to mono...
International audienceWe consider the task of under-determined reverberant audio source separation. ...
In this paper, unsupervised learning is used to separate percussive and harmonic sounds from monaura...
International audienceThis paper considers the blind separation of the harmonic and percussive compo...
International audienceWe address the problem of blind audio source separation in the under-determine...
We consider the task of under-determined and determined reverberant audio source separation, that is...
International audienceThis paper addresses the problem of multi-pitch estimation, which consists in ...
The structured arrangement of sounds in musical pieces, results in the unique creation of complex ac...
International audienceThis paper introduces a new harmonic/percussive source separation (HPSS) metho...
In a situation where multiple sound sources are concurrently active, the signals of the individual s...
Abstract—We consider inference in a general data-driven ob-ject-based model of multichannel audio da...
International audienceThis article addresses the problem of multichannel music separation. We propos...
International audienceThe separation of under-determined convolutive audio mixtures is generally add...
This thesis presents techniques for the modelling of musical signals, with particular regard to mono...
International audienceWe consider the task of under-determined reverberant audio source separation. ...
In this paper, unsupervised learning is used to separate percussive and harmonic sounds from monaura...
International audienceThis paper considers the blind separation of the harmonic and percussive compo...
International audienceWe address the problem of blind audio source separation in the under-determine...
We consider the task of under-determined and determined reverberant audio source separation, that is...
International audienceThis paper addresses the problem of multi-pitch estimation, which consists in ...
The structured arrangement of sounds in musical pieces, results in the unique creation of complex ac...
International audienceThis paper introduces a new harmonic/percussive source separation (HPSS) metho...
In a situation where multiple sound sources are concurrently active, the signals of the individual s...
Abstract—We consider inference in a general data-driven ob-ject-based model of multichannel audio da...
International audienceThis article addresses the problem of multichannel music separation. We propos...
International audienceThe separation of under-determined convolutive audio mixtures is generally add...
This thesis presents techniques for the modelling of musical signals, with particular regard to mono...
International audienceWe consider the task of under-determined reverberant audio source separation. ...
In this paper, unsupervised learning is used to separate percussive and harmonic sounds from monaura...