Authors:Baptiste Caramiaux, Frédéric Bevilacqua, Caroline Palmer and Marcelo M. Wanderley
Publication or Conference Title:Proceedings of 4th International Conference on Movement Computing (MOCO)
Expert musicians’ performances embed a timing variability pattern that can be used to recognize individual performance. However, it is not clear if such a property of performance variability is a consequence of learning or an intrinsic characteristic of human performance. In addition, little evidence exists about the role of timing and motion in recognizing individual music performance. In this paper we investigate these questions in the context of piano playing. We conducted a study during which we asked non-musicians to perform a musical sequence at different speeds. Then we tested their learning performance at a fixed tempo. Focusing on the possibility to identify the participant based on performance features of timing and motion variability, we show that participant classification increases with practice. This suggests that 1) the individual timing signatures are affected by learning and 2) timing and motion variability is structured. Moreover, we show that motion features better classify individual performances than timing features.