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Communication Dans Un Congrès Année : 2010

Partial Clustering Using a Time-Varying Frequency Model for Singing Voice 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.
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Dates et versions

hal-00662323 , version 1 (25-01-2012)

Identifiants

  • HAL Id : hal-00662323 , version 1

Citer

Lise Regnier, Geoffroy Peeters. Partial Clustering Using a Time-Varying Frequency Model for Singing Voice Detection.. ICASSP, Mar 2010, Dallas, United States. pp.1. ⟨hal-00662323⟩

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