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Drum controllers designed by researchers and commercial companies use a variety of techniques for capturing percussive gestures. It is challenging to obtain both quick response times and low-level data (such as position) that contain expressive information. This research is a comprehensive study of current methods to evaluate the available strategies and technologies. This study aims to demonstrate the benefits and detriments of the current state of percussion controllers as well as yield tools for those who would wish to conduct this type of study in the future.

This chapter gives an introduction into basic strands of current research in expressive music performance. A special focus is given on the various methods to acquire performance data either during a performance (e.g., through computer-monitored instruments) or from audio recordings. We then overview the different computational approaches to formalise and model the various aspects in expressive music performance. Future challenges and open problems are tackled briefly at the end of this chapter. 1.1

Musicians often make gestures and move their bodies expressing the musical intention. This visual information provides a channel of communication to the listener of its own, separated from the auditory signal. In order to explore to what extent emotional intentions can be conveyed through musicians ’ movements, subjects watched and rated silent video clips of musicians performing four different emotional intentions, Happy, Sad, Angry, and Fearful. In a first experiment twenty subjects were asked to rate performances on the marimba with respect to perceived emotional content and movement character. Video clips were presented in different viewing conditions, showing selected parts of the player. The results showed that the intentions Happiness, Sadness and Anger were well communicated, while Fear was not. The identification of the intended emotion was only slightly influenced by viewing condition. The movement ratings indicated that observers used cues to distinguish between intentions. In a second experiment subjects rated the same emotional intentions and movement character for woodwind performances, one bassoon player and one soprano saxophonist. The ratings from the second experiment confirmed that Fear was not communicated while Happiness, Sadness and Anger were recognized. The movement cues used by the subjects in the first experiment appeared also in the second experiment and were similar to cues in audio signals conveying emotions in music performance.

This paper presents the analysis of percussion technique for the simulation of virtual timpani playing situations. The analysis has been processed for two subjects performing with two types of grips (French and German), yielding to the extraction of percussion technique parameters from a motion capture database. These parameters are shown to be necessary for specifying the control and extending the expressivity of the simulation process.

synthesis by simulation of percussive gesture of a

Abstract. The understanding of different bowing strategies can provide key concepts for the modelling of music performance. We report here an exploratory study of bowing gestures for a viola player and a violin player in the case of bow strokes performed at different frequencies. Bow and arm movements as well as bow pressure on strings were measured respectively with a 3D optical motion capture system and a custom pressure sensor. While increasing bow stroke frequency, defined as the inverse time between two strokes, players did use different bowing movements as indicated from the measurement of bow velocity and arm joint angles. First, bow velocity profiles abruptly shift from a rectangle shape to a sinus shape. Second, while bow velocity is sinusoidal, an additional change is observed: the wrist and elbow relative phase shifts from out-of-phase to in-phase at the highest frequencies, indicating a possible change in the players coordinative pattern. We finally discuss the fact that only small differences are found in the sound while significant changes occur in the velocity / acceleration profiles. 1