Bridging the prosody GAP: Genetic Algorithm with People to efficiently
sample emotional prosody
- URL: http://arxiv.org/abs/2205.04820v1
- Date: Tue, 10 May 2022 11:45:15 GMT
- Title: Bridging the prosody GAP: Genetic Algorithm with People to efficiently
sample emotional prosody
- Authors: Pol van Rijn and Harin Lee and Nori Jacoby
- Abstract summary: 'Genetic Algorithm with People' (GAP) integrates human decision and production into a genetic algorithm.
We demonstrate that GAP can efficiently sample from the emotional speech space and capture a broad range of emotions.
GAP is language-independent and supports large crowd-sourcing, thus can support future large-scale cross-cultural research.
- Score: 1.2891210250935146
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: The human voice effectively communicates a range of emotions with nuanced
variations in acoustics. Existing emotional speech corpora are limited in that
they are either (a) highly curated to induce specific emotions with predefined
categories that may not capture the full extent of emotional experiences, or
(b) entangled in their semantic and prosodic cues, limiting the ability to
study these cues separately. To overcome this challenge, we propose a new
approach called 'Genetic Algorithm with People' (GAP), which integrates human
decision and production into a genetic algorithm. In our design, we allow
creators and raters to jointly optimize the emotional prosody over generations.
We demonstrate that GAP can efficiently sample from the emotional speech space
and capture a broad range of emotions, and show comparable results to
state-of-the-art emotional speech corpora. GAP is language-independent and
supports large crowd-sourcing, thus can support future large-scale
cross-cultural research.
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