Audience Interaction in Networked Audio Performance

A networked audio performance environment which mixes the moods of audience members via an artificial agent conductor to form a diverse acoustic ecology based on the auditory display of their mood data. Audience members input their moods to start the performance and a reinforcement learning engine offers participants the opportunity to improve the validity of audio-to-mood mapping.



Jack Stockholm, Philippe Pasquier.

Research papers

Stockholm, J. & Pasquier, P. (2008). “Eavesdropping: Audience Interaction in Networked Audio Performance” ACM International Conference on Multimedia (ACM MM 2008), Vancouver, Canada, pages 559-568.

Download PDF

Stockholm, J. (2008). “Eavesdropping: Network Mediated Performance in Social Space.” Leonardo Music Journal, 18 (2008): 55-58.

Download PDF

Stockholm, J. & Pasquier, P. (2009). “Reinforcement Learning of Listener Response for Mood Classification of Audio” Proceedings of the First International Workshop on Social Behavior in Music (in conjonction with the IEEE conference on Social Computing).

Download PDF