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Partial Clustering Using a Time-Varying Frequency Model for Singing Voice Detection.

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text
 

Genre(s)

article
 

Forme(s)

document numérique
 

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Titre

Partial Clustering Using a Time-Varying Frequency Model for Singing Voice Detection.
 

Nom(s)

Regnier, lise (auteur)
 
Peeters, Geoffroy (auteur)
 

Publication

2010
 

Description

Sujet(s)

Singing voice detection   Source separation   Polyphonic music analysis   Vibrato detection.
 

Résumé

We propose a new method to group partials produced by each instrument of a polyphonic audio mixture. This method works for pitched and harmonic instruments and is specially adapted to singing voice. In our approach, we model time-varying frequencies of partials as a slowly varying frequency plus a sinusoidal modulation. The parameters obtained with this model plus some common Auditory Scene Analysis principles are used to define a similarity measure between partials. This multi-criterion based measure is then used to build the input similarity matrix of a clustering algorithm. Clusters obtained are groups of harmonically related partials. We evaluate the ability of our method to group partials per source when one of the sources is a singing voice. We show that partial clustering is a promising approach for singing voice detection and separation.
 

Note(s)

Contribution au colloque ou congrès : ICASSP
 

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Date de la notice

2010-02-25 01:00:00
 

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