Analyzing Visible Articulatory Movements in Speech Production For Speech-Driven 3D Facial Animation

Speech-driven 3D facial animation aims to generate realistic facial meshes based on input speech signals. However, due to a lack of understanding of visible articulatory movements, current state-of-the-art methods result in inaccurate lip and jaw movements. Traditional evaluation metrics, such as lip vertex error (LVE), often fail to represent the quality of visual results. Based on our observation, we reveal the problems with existing evaluation metrics and raise the necessity for separate evaluation approaches for 3D axes. Comprehensive analysis shows that most recent methods struggle to precisely predict lip and jaw movements in 3D space.

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Publication Details

Published
2024-09-27
DOI
https://doi.org/10.1109/icip51287.2024.10647359
Primary Topic
Face recognition and analysis
Type
article
Field-Weighted Citation Impact
0.00

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article

Analyzing Visible Articulatory Movements in Speech Production For Speech-Driven 3D Facial Animation

Hak Gu Kim, Sangmin Lee, Hyung Kyu Kim
Face recognition and analysis
article

Analyzing Visible Articulatory Movements in Speech Production For Speech-Driven 3D Facial Animation

Hak Gu Kim, Sangmin Lee, Hyung Kyu Kim
article en

Abstract

Speech-driven 3D facial animation aims to generate realistic facial meshes based on input speech signals. However, due to a lack of understanding of visible articulatory movements, current state-of-the-art methods result in inaccurate lip and jaw movements. Traditional evaluation metrics, such as lip vertex error (LVE), often fail to represent the quality of visual results. Based on our observation, we reveal the problems with existing evaluation metrics and raise the necessity for separate evaluation approaches for 3D axes. Comprehensive analysis shows that most recent methods struggle to precisely predict lip and jaw movements in 3D space.

University of Illinois Urbana-Champaign (US), Chung-Ang University (KR)
National Research Foundation
Openalex Percentile: Top 84%
Face recognition and analysis
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