Enhancing Portuguese Sign Language Animation with Dynamic Timing and Mouthing
Lacerda, Inês, Nicolau, Hugo, Coheur, Luisa
–arXiv.org Artificial Intelligence
Current signing avatars are often described as unnatural as they cannot accurately reproduce all the subtleties of synchronized body behaviors of a human signer. In this paper, we propose a new dynamic approach for transitions between signs, focusing on mouthing animations for Portuguese Sign Language. Although native signers preferred animations with dynamic transitions, we did not find significant differences in comprehension and perceived naturalness scores. On the other hand, we show that including mouthing behaviors improved comprehension and perceived naturalness for novice sign language learners. Results have implications in computational linguistics, human-computer interaction, and synthetic animation of signing avatars.
arXiv.org Artificial Intelligence
Jul-12-2023
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