Recognition and Prediction in a Network Music Performance System for Indian Percussion

by Mihir Sarkar and Barry Vercoe
International Conference on New Interfaces for Musical Expression (NIME 2007), New York, NY, USA, June 6-9, 2007.

Playing music over the Internet, whether for real-time jamming, distributed performance or distance education, is constrained by the network latency which introduces, over long distances, time delays unsuitable for musical applications. Current musical collaboration systems generally transmit compressed audio streams over low-latency and high-bandwidth networks to optimize musician synchronization. This paper proposes an alternative approach based on pattern recognition and music prediction. Trained for a particular type of music, here the Indian tabla drum, the system called TablaNet identifies rhythmic patterns by recognizing individual strokes played by a musician and mapping them dynamically to known musical constructs. Symbols representing these musical structures are sent over the network to a corresponding computer system. The computer at the receiving end anticipates incoming events by analyzing previous phrases and synthesizes an estimated audio output. Although such a system may introduce variants due to prediction approximations, resulting in a slightly different musical experience at both ends, we find that it demonstrates a high level of playability with an immediacy not present in other systems, and functions well as an educational tool.

Paper (PDF): 4 pages (608 KB)