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In this paper we investigate the problem of locating singing voice in music tracks. As opposed to most existing methods for this task, we rely on the extraction of the characteristics specific to singing voice. In our approach we suppose that the singing voice is characterized by harmonicity, formants, vibrato and tremolo. In the present study we deal only(More)
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(More)
In this paper we investigate the problem of singer identification on acapella recordings of isolated notes. Most of studies on singer identification describe the content of signals of singing voice with features related to the timbre (such as MFCC or LPC). These features aim to describe the behavior of frequencies at a given instant of time (local(More)
This paper proposes a method to verify the singer identity of a given song. The query song is modeled as a GMM learned on the features extracted from sustained sung notes of the song. Each note is described by the shape its spectral envelope and by the temporal variations in frequency and amplitude of its fundamental frequency. The singer identity is(More)
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