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research-article

Gesture Motion Graphs for Few-Shot Speech-Driven Gesture Reenactment

Authors:

Shuwu ZhangAuthors Info & Claims

ICMI '23: Proceedings of the 25th International Conference on Multimodal Interaction

Pages 772 - 778

https://doi.org/10.1145/3577190.3616118

Published: 09 October 2023 Publication History

Abstract

This paper presents the CASIA-GO entry to the Generation and Evaluation of Non-verbal Behaviour for Embedded Agents (GENEA) Challenge 2023. The system is originally designed for few-shot scenarios such as generating gestures with the style of any in-the-wild target speaker from short speech samples. Given a group of reference speech data including gesture sequences, audio, and text, it first constructs a gesture motion graph that describes the soft gesture units and interframe continuity inside the speech, which is ready to be used for new rhythmic and semantic gesture reenactment by pathfinding when test audio and text are provided. We randomly choose one clip from the training data for one test clip to simulate a few-shot scenario and provide compatible results for subjective evaluations. Despite the 0.25% average utilization of the whole training set for each clip in the test set and the 17.5% total utilization of the training set for the whole test set, the system succeeds in providing valid results and ranks in the top 1/3 in the appropriateness for agent speech evaluation.

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Cited By

Tonoli RCosta PMarques LUeda L(2024)Gesture Area Coverage to Assess Gesture Expressiveness and Human-LikenessCompanion Proceedings of the 26th International Conference on Multimodal Interaction10.1145/3686215.3688822(165-169)Online publication date: 4-Nov-2024
https://dl.acm.org/doi/10.1145/3686215.3688822
Kucherenko TNagy RYoon YWoo JNikolov TTsakov MHenter G(2023)The GENEA Challenge 2023: A large-scale evaluation of gesture generation models in monadic and dyadic settingsProceedings of the 25th International Conference on Multimodal Interaction10.1145/3577190.3616120(792-801)Online publication date: 9-Oct-2023
https://dl.acm.org/doi/10.1145/3577190.3616120

Index Terms

Gesture Motion Graphs for Few-Shot Speech-Driven Gesture Reenactment
1. Computing methodologies
  1. Computer graphics
    1. Animation
2. Human-centered computing
  1. Human computer interaction (HCI)

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Information & Contributors

Information

Published In

cover image ACM Conferences

ICMI '23: Proceedings of the 25th International Conference on Multimodal Interaction

October 2023

858 pages

ISBN:9798400700552

DOI:10.1145/3577190

Editors:
Elisabeth André
University of Augsburg
,
Mohamed Chetouani
Sorbonne University
,
Dominique Vaufreydaz
Univ. Grenoble Alpes
,
Gale Lucas
USC Institute for Creative Technologies
,
Tanja Schultz
University of Bremen
,
Louis-Philippe Morency
Carnegie Mellon University
,
Alessandro Vinciarelli
University of Glasgow

Copyright © 2023 ACM.

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SIGCHI: ACM Special Interest Group on Computer-Human Interaction

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 09 October 2023

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Refereed limited

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National Key Research and Development Program of China

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ICMI '23

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SIGCHI

ICMI '23: INTERNATIONAL CONFERENCE ON MULTIMODAL INTERACTION

October 9 - 13, 2023

Paris, France

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Overall Acceptance Rate 453 of 1,080 submissions, 42%

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Cited By

Tonoli RCosta PMarques LUeda L(2024)Gesture Area Coverage to Assess Gesture Expressiveness and Human-LikenessCompanion Proceedings of the 26th International Conference on Multimodal Interaction10.1145/3686215.3688822(165-169)Online publication date: 4-Nov-2024
https://dl.acm.org/doi/10.1145/3686215.3688822
Kucherenko TNagy RYoon YWoo JNikolov TTsakov MHenter G(2023)The GENEA Challenge 2023: A large-scale evaluation of gesture generation models in monadic and dyadic settingsProceedings of the 25th International Conference on Multimodal Interaction10.1145/3577190.3616120(792-801)Online publication date: 9-Oct-2023
https://dl.acm.org/doi/10.1145/3577190.3616120

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