activity
20182025
most citedSpeech Gesture Generation from the Trimodal Context of Text, Audio, and Speaker Identity

321 citations · 504 across the 7 of their papers we have counts for

collaborators

7 papers

cs.RO2025

Learning Dexterous Bimanual Catch Skills through Adversarial-Cooperative Heterogeneous-Agent Reinforcement Learning

Taewoo Kim, Youngwoo Yoon, Jaehong Kim

Robotic catching has traditionally focused on single-handed systems, which are limited in their ability to handle larger or more complex objects. In contrast, bimanual catching off…

cs.AI2024

LoTa-Bench: Benchmarking Language-oriented Task Planners for Embodied Agents

Jae-Woo Choi, Youngwoo Yoon, Hyobin Ong +2

Large language models (LLMs) have recently received considerable attention as alternative solutions for task planning. However, comparing the performance of language-oriented task…

cs.HC2022★ 87 cited

The GENEA Challenge 2022: A large evaluation of data-driven co-speech gesture generation

Youngwoo Yoon, Pieter Wolfert, Taras Kucherenko +4

This paper reports on the second GENEA Challenge to benchmark data-driven automatic co-speech gesture generation. Participating teams used the same speech and motion dataset to bui…

cs.HC2021★ 69 cited

A large, crowdsourced evaluation of gesture generation systems on common data: The GENEA Challenge 2020

Taras Kucherenko, Patrik Jonell, Youngwoo Yoon +2

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 embo…

cs.HC2021★ 21 cited

HEMVIP: Human Evaluation of Multiple Videos in Parallel

Patrik Jonell, Youngwoo Yoon, Pieter Wolfert +2

In many research areas, for example motion and gesture generation, objective measures alone do not provide an accurate impression of key stimulus traits such as perceived quality o…

cs.GR2020★ 321 cited

Speech Gesture Generation from the Trimodal Context of Text, Audio, and Speaker Identity

Youngwoo Yoon, Bok Cha, Joo-Haeng Lee +4

For human-like agents, including virtual avatars and social robots, making proper gestures while speaking is crucial in human--agent interaction. Co-speech gestures enhance interac…

cs.RO2018★ 6 cited

Robots Learn Social Skills: End-to-End Learning of Co-Speech Gesture Generation for Humanoid Robots

Youngwoo Yoon, Woo-Ri Ko, Minsu Jang +3

Co-speech gestures enhance interaction experiences between humans as well as between humans and robots. Existing robots use rule-based speech-gesture association, but this requires…