Singer verification: Singer model .vs. song model

Abstract

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 verified with two approaches: the model of the query song is compared to a singer-based GMM or compared to the GMM of another song performed by the same singer. The comparison is done using a dissimilarity measurement given by the Kullback Leibler divergence. When the two types of features are combined, the proposed approach verifies the singer identity of a given a cappella song with an error rate lower than 8% when the whole song is considered and an error rate lower than 10% when a short excerpt of the song (i.e. 15 consecutive sustained notes) is considered.

Singer identification using perceptual features and cepstral coefficients of an audio signal from Indian video songs

“…There is no efficient algorithm which works fine on speech identification and singing voice characterization together. So information on the singer's voice is essential to organize, extract, and classify music collections [5]. Sometimes, a viewer is interested to hear Indian video songs based on their interest like favorite playback singer, actor, and actress.…”

A stochastic model of singing voice F0 contours for characterizing expressive dynamic components

“…Most previous papers have reported that these dynamic components strongly affect singing-voice perception, and that the former relates to the naturalness and individuality of a singing voice while the latter relates to singing styles and skills [4]. Accordingly, extracting these components from a raw F 0 contour automatically can be potentially very beneficial for any singing voice applications, such as singer identification, singing skill evaluation and the synthesis of more natural and varied singing voices [5,6,7].…”