Title:
Empirically Informed Sound Synthesis Application for Enhancing the Perception of Expressive Robotic Movement
Empirically Informed Sound Synthesis Application for Enhancing the Perception of Expressive Robotic Movement
Author(s)
Bellona, Jon
Bai, Lin
Dahl, Luke
LaViers, Amy
Bai, Lin
Dahl, Luke
LaViers, Amy
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Abstract
Since people often communicate internal states and intentions
through movement, robots can better interact with humans if they
too can modify their movements to communicate changing state.
These movements, which may be seen as supplementary to those
required for workspace tasks, may be termed “expressive.” However,
robot hardware, which cannot recreate the same range of dynamics
as human limbs, often limit expressive capacity. One solution
is to augment expressive robotic movement with expressive
sound.
To that end, this paper presents an application for synthesizing
sounds that match various movement qualities. Its design is
based on an empirical study analyzing sound and movement qualities,
where movement qualities are parametrized according to Laban’s
Effort System. Our results suggests a number of correspondences
between movement qualities and sound qualities. These
correspondences are presented here and discussed within the context
of designing movement-quality-to-sound-quality mappings in
our sound synthesis application. This application will be used in
future work testing user perceptions of expressive movements with
synchronous sounds.
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Date Issued
2017-06
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Proceedings
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This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.