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학술대회 A Large, Crowdsourced Evaluation of Gesture Generation Systems on Common Data: The GENEA Challenge 2020
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저자
Taras Kucherenko, Patrik Jonell, 윤영우, Pieter Wolfert, Gustav Eje Henter
발행일
202104
출처
International Conference on Intelligent User Interfaces (IUI) 2021, pp.11-21
DOI
https://dx.doi.org/10.1145/3397481.3450692
초록
Co-speech gestures, gestures that accompany speech, play an important role in human communication. Automatic co-speech gesture generation is thus a key enabling technology for embodied conversational agents (ECAs), since humans expect ECAs to be capable of multi-modal communication. Research into gesture generation is rapidly gravitating towards data-driven methods. Unfortunately, individual research efforts in the field are difficult to compare: There are no established benchmarks, and each study tends to use its own dataset, motion visualisation, and evaluation methodology. To address this situation, we launched the GENEA Challenge, a gesture-generation challenge wherein participating teams built automatic gesture-generation systems on a common dataset, and the resulting systems were evaluated in parallel in a large, crowdsourced user study using the same motion-rendering pipeline. Since differences in evaluation outcomes between systems now are solely attributable to differences between the motion-generation methods, this enables benchmarking recent approaches against one another in order to get a better impression of the state of the art in the field. This paper reports on the purpose, design, results, and implications of our challenge.
키워드
conversational agents, evaluation paradigms, gesture generation
KSP 제안 키워드
Common data, Embodied Conversational Agents(ECAs), Enabling technologies, Generation system, Gesture generation, Multi-modal communication, Rendering Pipeline, User study, crowdsourced evaluation, data-driven method, evaluation methodology