This study presents an effective technique for automatically identifying the singer of a music recording. Since the vast majority of popular music contains background accompaniment during most or all vocal passages, directly acquiring isolated solo voice data for extracting the singer's vocal characteristics is usually infeasible. To eliminate the interference of background music for singer identification, we leverage statistical estimation of a piece's musical background to build a reliable model for the solo voice. Validity of the proposed singer identification system is confirmed via the experimental evaluations conducted on a 23-singer pop music database.