Automatic singer identification

The singer´s information is essential in organizing, browsing and retrieving music collections. In this paper, a system for automatic singer identification is developed which recognizes the singer of a song by analyzing the music signal. Meanwhile, songs which are similar in terms of singer´s voice are clustered. The proposed scheme follows the framework of common speaker identification systems, but special efforts are made to distinguish the singing voice from instrumental sounds in a song. A statistical model is trained for each singer´s voice with typical song(s) of the singer. Then, for a song to be identified, the starting point of singing voice is detected and a portion of the song is excerpted from that point. Audio features are extracted and matched with singers´ voice models in the database. The song is assigned to the model having the best match. Promising results are obtained on a small set of samples, and accuracy rates of around 80% are achieved.