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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zbyszynski_gestureTimbre_final.pdf - Accepted Version Available under License Creative Commons Attribution Non-commercial. Download (2MB) | Preview |
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) |
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Departments, Centres and Research Units: |
Computing |
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Dates: |
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Event Location: |
Marseille, France |
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Date range: |
14-18 October 2019 |
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Item ID: |
26869 |
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Date Deposited: |
10 Sep 2019 11:31 |
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Last Modified: |
13 Jun 2021 16:05 |
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URI: |
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