- B. Raj. 2006. SEPARATING A FOREGROUND SINGER FROM. Abstract: In this paper we present a algorithm for separating singing voices from background music in popular songs. The algorithm is derived by modelling the magnitude spectrogram of audio signals as the outcome of draws from a discrete bi-variate random process that generates time-frequency pairs. The spectrogram of a song is assumed to have been obtained through draws from the distributions underlying the music and the vocals, respectively. The parameters of the underlying distribuiton are learnt from the observed spectrogram of the song. The spectrogram of the separated vocals is then derived by estimating the fraction of draws that were obtained from its distribution. In the paper we present the algorithm within a framework that allows personalization of popular songs, by separating out the vocals, processing them appropriately to one’s own tastes, and remixing them. Our experiments reveal that we are effectively able to separate out the vocals in a song and personalize them to our tastes.
