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BioMusic

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Balandino Di Donato
added 2 research items
In this paper, we consider the effect of co-adaptive learning on the training and evaluation of real-time, interactive machine learning systems, referring to specific examples in our work on action-perception loops, feedback for virtual tasks, and training of regression and temporal models. Through these studies we have encountered challenges when designing and assessing expressive, multimodal interactive systems. We discuss those challenges to machine learning and human-computer interaction, proposing future directions and research.
This paper presents a method for mapping embodied gesture , acquired with electromyography and motion sensing, to a corpus of small sound units, organised by derived timbral features using concatenative synthesis. Gestures and sounds can be associated directly using individual units and static poses, or by using a sound tracing method that leverages our intuitive associations between sound and embodied movement. We propose a method for augmenting corporal density to enable expressive variation on the original gesture-timbre space.