activity
20182022
most citedSpeech Gesture Generation from the Trimodal Context of Text, Audio, and Speaker Identity

321 citations · 364 across the 8 of their papers we have counts for

collaborators

8 papers

cs.RO2022

Nonverbal Social Behavior Generation for Social Robots Using End-to-End Learning

Woo-Ri Ko, Minsu Jang, Jaeyeon Lee +1

To provide effective and enjoyable human-robot interaction, it is important for social robots to exhibit nonverbal behaviors, such as a handshake or a hug. However, the traditional…

cs.HC2021★ 20 cited

SGToolkit: An Interactive Gesture Authoring Toolkit for Embodied Conversational Agents

Youngwoo Yoon, Keunwoo Park, Minsu Jang +2

Non-verbal behavior is essential for embodied agents like social robots, virtual avatars, and digital humans. Existing behavior authoring approaches including keyframe animation an…

eess.AS2021★ 1 cited

VOTE400(Voide Of The Elderly 400 Hours): A Speech Dataset to Study Voice Interface for Elderly-Care

Minsu Jang, Sangwon Seo, Dohyung Kim +3

This paper introduces a large-scale Korean speech dataset, called VOTE400, that can be used for analyzing and recognizing voices of the elderly people. The dataset includes about 3…

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.RO2020★ 2 cited

AIR-Act2Act: Human-human interaction dataset for teaching non-verbal social behaviors to robots

Woo-Ri Ko, Minsu Jang, Jaeyeon Lee +1

To better interact with users, a social robot should understand the users' behavior, infer the intention, and respond appropriately. Machine learning is one way of implementing rob…

cs.RO2020★ 5 cited

ETRI-Activity3D: A Large-Scale RGB-D Dataset for Robots to Recognize Daily Activities of the Elderly

Jinhyeok Jang, Dohyung Kim, Cheonshu Park +3

Deep learning, based on which many modern algorithms operate, is well known to be data-hungry. In particular, the datasets appropriate for the intended application are difficult to…

cs.RO2019★ 9 cited

Cut-and-Paste Dataset Generation for Balancing Domain Gaps in Object Instance Detection

Woo-han Yun, Taewoo Kim, Jaeyeon Lee +2

Training an object instance detector where only a few training object images are available is a challenging task. One solution is a cut-and-paste method that generates a training d…

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…