Learning to play like the great pianists
Asmir Tobudic, Gerhard Widmer · 2005
An application of relational instance-based learning to the complex task of expressive music performance is presented. We investigate to what extent a machine can automatically build ‘expressive profiles ’ of famous pianists using only minimal performance information extracted from audio CD recordings by pianists and the printed score of the played music. It turns out that the machine-generated expressive performances on unseen pieces are substantially closer to the real performances of the ‘trainer ’ pianist than those of all others. Two other interesting applications of the work are discussed: recognizing pianists from their style of playing, and automatic style replication.