DC Field | Value | Language |
---|---|---|
dc.contributor.author | Kucherenko, Taras | ko |
dc.contributor.author | Jonell, Patrik | ko |
dc.contributor.author | Yoon, Youngwoo | ko |
dc.contributor.author | Wolfert, Pieter | ko |
dc.contributor.author | Henter, Gustav Eje | ko |
dc.date.accessioned | 2021-11-03T06:48:28Z | - |
dc.date.available | 2021-11-03T06:48:28Z | - |
dc.date.created | 2021-10-26 | - |
dc.date.issued | 2021-04 | - |
dc.identifier.citation | 26th International Conference on Intelligent User Interfaces: Where HCI Meets AI, IUI 2021, pp.11 - 21 | - |
dc.identifier.uri | http://hdl.handle.net/10203/288667 | - |
dc.description.abstract | 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. | - |
dc.language | English | - |
dc.publisher | Association for Computing Machinery | - |
dc.title | A Large, Crowdsourced Evaluation of Gesture Generation Systems on Common Data: The GENEA Challenge 2020 | - |
dc.type | Conference | - |
dc.identifier.scopusid | 2-s2.0-85102546745 | - |
dc.type.rims | CONF | - |
dc.citation.beginningpage | 11 | - |
dc.citation.endingpage | 21 | - |
dc.citation.publicationname | 26th International Conference on Intelligent User Interfaces: Where HCI Meets AI, IUI 2021 | - |
dc.identifier.conferencecountry | US | - |
dc.identifier.conferencelocation | Texas | - |
dc.identifier.doi | 10.1145/3397481.3450692 | - |
dc.contributor.localauthor | Yoon, Youngwoo | - |
dc.contributor.nonIdAuthor | Kucherenko, Taras | - |
dc.contributor.nonIdAuthor | Jonell, Patrik | - |
dc.contributor.nonIdAuthor | Wolfert, Pieter | - |
dc.contributor.nonIdAuthor | Henter, Gustav Eje | - |
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