On the Computer Recognition of Solo Piano Music

We present work towards a computer system for the automatic transcription of piano performances. The system takes audio files containing polyphonic piano music as input, and produces MIDI output, representing the pitch, timing and volume of the musical notes. The aim of this work is not to reduce the performance data to common music notation, but to extract the performance parameters for a quantitative study of musical expression in piano performance. Standard signal processing techniques based on the short time Fourier transform are used to create a time-frequency representation of the signal, and adaptive peak-picking and pattern matching algorithms are employed to find the musical notes. In order to perform large scale testing, the test process is automated by synthesizing audio data from MIDI files using high quality sofware synthesis, and comparing results with the original MIDI data. The test data used is Mozart piano sonatas performed by a concert pianist.