A Correntropy-Based Voice to MIDI Transcription Algorithm

In this paper we describe an automatic voice-to-MIDI transcription procedure. In particular we propose a note segmentation method based on the analysis of the signal envelope and its derivative. The pitch of the segmented note is extracted with a novel generalized correlation function called Correntropy function achieving high accuracy with the same computational cost of traditional correlation based methods. The performances of our transcription system have been measured on examples extracted by some repositories available on internet; they consist in sung melodies and hummed queries. Results show the ability of our transcription procedure to cope with query-by-humming systems, as well as with monophonic singing transcription. Performances can be easily evaluated by downloading from the authors web site the original PCM files and the corresponding MIDI files produced by the proposed transcription algorithm.