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OFAI-TR-2004-04 ( 180kB g-zipped PostScript file,  280kB PDF file)

Automatic Recognition of Famous Artists by Machine

Gerhard Widmer, Patrick Zanon

The paper addresses the question whether it is possible for a machine to learn to distinguish and recognise famous musicians (concert pianists), based on their style of playing. We extract a number of low-level features related to expressive timing and dynamics from the original audio CD recordings by famous pianists, and apply various machine learning algorithms to the task of learning classifiers based on these features. Experiments show that the computer can learn to identify the performer in a new recording with a probability significantly higher than chance, despite the fact that the features only capture a very limited amount of information about a performance. An analysis of the learned classifiers reveals a number of performance features that seem particularly relevant to style differentiation, and an application of the classifiers to music of a very different style shows that the machine seems to have captured truly fundamental aspects of artistic style. One limitation of the current approach is that sequential information is totally ignored, and we briefly report on ongoing work that tries to address this problem via an interesting conversion of music performances to strings.

Keywords: machine learning, music

Citation: Widmer G., Zanon P.: Automatic Recognition of Famous Artists by Machine. Technical Report, Österreichisches Forschungsinstitut für Artificial Intelligence, Wien, TR-2004-04, 2004