Data Anticipation for Gesture Recognition in the Air Percussion

Vincent Goudard (1, 2) , Christophe Havel (2) , Sylvain Marchand (2) , Myriam Desainte-Catherine (2)

1 STMS - Sciences et Technologies de la Musique et du Son
2 LaBRI - Laboratoire Bordelais de Recherche en Informatique

The use of computers as Digital Musical Instruments (DMI) rises many problems due to the separation between gesture and sound production. However, computational power allows now for complex real-time analysis and gesture anticipation and recognition. We present here an interactive performance system for a percussionist playing in the air, with no physical percussion. Since the gesture sensors are not perfect, we have to deal with unreliable data. And since we expect a real-time sound synthesis synchronous with the strikes of the percussionist, we have to anticipate his gesture to some extent, in order to forecast his strikes, because we cannot wait for the strikes to occur without degrading the auditory feedback. We show that the use of linear prediction can help to both correct the data from the gesture sensors and anticipate the gesture of the percussionist. The difficult problem of gesture recognition is also discussed in the context of the “air percussion” project.

Domaines: Autre [cs.OH]

Vincent Goudard, Christophe Havel, Sylvain Marchand, Myriam Desainte-Catherine. Data Anticipation for Gesture Recognition in the Air Percussion. Proceedings of the International Computer Music Conference (ICMC05), Sep 2005, Spain. pp.49--52. ⟨hal-00307897⟩