A case based approach to expressivity-aware tempo transformation

The research presented in this paper is focused on global tempo transformations of music performances. We are investigating the problem of how a performance played at a particular tempo can be rendered automatically at another tempo, while preserving naturally sounding expressivity. Or, differently stated, how does expressiveness change with global tempo. Changing the tempo of a given melody is a problem that cannot be reduced to just applying a uniform transformation to all the notes of a musical piece. The expressive resources for emphasizing the musical structure of the melody and the affective content differ depending on the performance tempo. We present a case-based reasoning system called TempoExpress and will describe the experimental results obtained with our approach.

• Type: Journal
• Year: 2006
• Where: ML
• Authors: Maarten Grachten, Josep Lluís Arcos, Ramon López de Mántaras
• Keywords: Global Tempo, Global Tempo Transformations, Machine Learning, ML 2006, Tempo