Gesture-Timbre Space: Multidimensional Feature Mapping Using Machine Learning & Concatenative Synthesis

Zbyszynski, Michael; Di Donato, Balandino and Tanaka, Atau. 2019. 'Gesture-Timbre Space: Multidimensional Feature Mapping Using Machine Learning & Concatenative Synthesis'. In: 14th International Symposium on Computer Music Multidisciplinary Research (CMMR). Marseille, France 14-18 October 2019. [Conference or Workshop Item]

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Abstract or Description

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.

Item Type:

Conference or Workshop Item (Paper)

Departments, Centres and Research Units:

Computing > Embodied AudioVisual Interaction Group (EAVI)


23 June 2019Accepted
14 October 2019Published

Event Location:

Marseille, France

Date range:

14-18 October 2019

Item ID:


Date Deposited:

10 Sep 2019 11:31

Last Modified:

13 Jun 2021 16:05


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