0000000001328017
AUTHOR
Panos Papiotis
showing 2 related works from this author
Inducing Rules of Ensemble Music Performance : A Machine Learning Approach
2013
Previous research in expressive music performance has described how solo musicians intuitively shape each note in relation to local/global score contexts. However, expression in ensemble performances, where each individual voice is played simultaneously with other voices, has been little explored. We present an exploratory study in which the performance of a string quartet is recorded and analysed by a computer. We use contact microphones to acquire four audio signals from which a set of audio descriptors is extracted individually for each musician. Moreover, we use motion capture to extract bowing descriptors (bow velocity/force) from each of the four performers. The gathered multimodal da…
Aural-Based Detection and Assessment of Real Versus Artificially Synchronized String Quartet Performance
2013
In a musical ensemble musicians can influence each other’s performance in terms not only of timing but also in other aspects of the performance such as dynamics, intonation, and timbre. The goal of this work is to test whether this influence can be perceived by a listener from an audio recording solely. We utilize a set of string quartet recordings where every piece is recorded in two experimental conditions: the solo condition, where each musician performs alone; and the ensemble condition, where the musicians perform together after a brief rehearsal. Using state-of-the-art audio analysis/synthesis methods, we artificially synchronize the record-ings in the solo condition note-by-note, thu…