AN AUTOMATED SINGING EVALUATION METHOD FOR KARAOKE SYSTEMS

Although many Karaoke systems come with a scoring feature that provides singers with a simple performance rating, the automated scoring, however, is either random or incomparable to that of human evaluation. This study exploits various acoustic features, including pitch, volume, and rhythm to assess a singing performance. We invited a number of singers having different levels of singing capabilities to record for Karaoke solo vocal samples. The performances were rated independently by four musicians, and then used in conjunction with additional Karaoke VCD music for the training of our proposed system. Our experiment shows that the results of automated singing evaluation are close to the human rating.