ECAI 2004 Conference Paper

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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. To that end, 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 performance style. Some pianists exhibit a particularly high degree of recognisability. 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 performances of 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 in the learning process, and we briefly report on ongoing work that tries to address this problem via an interesting conversion of music performances to strings.

Keywords: Art and Music, Machine Learning

Citation: Gerhard Widmer, Patrick Zanon: Automatic Recognition of Famous Artists by Machine. In R.López de Mántaras and L.Saitta (eds.): ECAI2004, Proceedings of the 16th European Conference on Artificial Intelligence, IOS Press, Amsterdam, 2004, pp.1109-1110.


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ECAI-2004 is organised by the European Coordinating Committee for Artificial Intelligence (ECCAI) and hosted by the Universitat Politècnica de València on behalf of Asociación Española de Inteligencia Artificial (AEPIA) and Associació Catalana d'Intel-ligència Artificial (ACIA).