Automatic transcription of polyphonic piano music using a note masking technique

This paper describes a polyphonic note detection system incorporating a simple masking technique that can accurately transcribe chords and polyphonic piano music. The system, developed in MATLAB, will take input files in .wav format. The music is segmented by using Note Average Energy (NAE) onset detection. Onsets are used to segment the music into note windows which are then analysed using the FFT. Following compilation of the frequency peaks in each note window, an iterative masking procedure is used to detect and successively extract the notes. The masking procedure uses a database of note masks which are compiled from multiple note examples using both monophonic and polyphonic examples.