Sylvie Gibet
Papers
3
Total Citations
19
H-Index
3
About
Sylvie Gibet is a leading researcher in the synthesis and animation of sign language, with a particular focus on French Sign Language (LSF). Her work bridges computer graphics, motion capture, and human-computer interaction to create more natural and expressive signing avatars—a critical tool for deaf communities to access information in their preferred language. Gibet’s major contributions include developing methods for motion synthesis and editing that enable the generation of novel sign language content from captured data, moving beyond rigid, procedural animations that users often reject as robotic or unnatural. Her co-creation of the LSF-ANIMAL corpus, a motion capture dataset specifically designed for avatar animation, provides a foundational resource for the field. While her citation counts (e.g., 9 for her 2021 synthesis paper, 6 for the LSF-ANIMAL corpus) reflect a specialized but impactful audience, her earlier work on biologically relevant models for controlling anthropomorphic limbs (2002, 4 citations) demonstrates a long-standing commitment to realism in movement generation. Gibet’s research is essential for anyone interested in accessible technology, embodied conversational agents, or the computational challenges of capturing the spatial-temporal richness of sign languages.
Research Focus
Key Achievements
Top Papers
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