This paper questions and examines the validity and future of interactive network performance. The history of research in the area is described as well as experiments with our own system. Our custom-built networked framework, known as GIGAPOPR, transfers high-quality audio, video and MIDI data over a network connection to enable live musical performances to occur in two or more distinct locations. One of our first sensor-augmented Indian instruments, The Electronic Dholak (EDholak) is a multi-player networked percussion controller that is modelled after the traditional Indian Dholak. The EDholaks trigger sound, including samples and physical models, and visualisation, using our custom-built networked visualisation software, known as veldt. 1.

Using sensors to extract gestural information for control parameters of digital audio effects is common practice. There has also been research using machine learning techniques to classify specific gestures based on audio feature analysis. In this paper, we will describe our experiments in training a computer to map the appropriate audio-based features to look like sensor data, in order to potentially eliminate the need for sensors. Specifically, we will show our experiments using the ESitar, a digitally enhanced sensor based controller modeled after the traditional North Indian sitar. We utilize multivariate linear regression to map continuous audio features to continuous gestural data. 1.