A compositional Multiple-F0 estimation algorithms for computer-synthesized music

Multiple fundamental frequency estimation, or Multiple-F0 estimation, is one of the most important problem on automatic music transcription, but it has not been well resolved up to now. This paper presents a machine learning methods using harmonic matching and iterative deletion for computer synthesized music specifically to Multiple-F0 estimation. Computer-synthesized music is almost free from similar instruments of the differences between different individuals, so it is a good research object. It can be shown in this paper that the experimental results indicate that this method has very good recognition results.