Singer Identification in Popular Music using Warped Linear Prediction

In most popular music, the vocals sung by the lead singer are the focal point of the song. The unique qualities of a singer’s voice make it relatively easy for us to identify a song as belonging to that particular artist. With little training, if one i s familiar with a particular singer’s voice one can usually recognize that voice in other pieces, even when hearing a song for the first time. The research presented in this paper attempts to automatically establish the identity of a singer using acoustic features extracted from songs in a database of popular music. As a first step, an untrained algorithm for automatically extracting vocal segments from within songs is presented. Once these vocal segments are identified, they are presented to a singer identification system that has been trained on data taken from other songs by the same artists in the database.