PESTalk: Speech-Driven 3D Facial Animation with Personalized Emotional Styles
October 13, 2025 Β· Declared Dead Β· π ACM Multimedia
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Authors
Tianshun Han, Benjia Zhou, Ajian Liu, Yanyan Liang, Du Zhang, Zhen Lei, Jun Wan
arXiv ID
2512.05121
Category
cs.GR: Graphics
Cross-listed
cs.AI
Citations
1
Venue
ACM Multimedia
Last Checked
3 months ago
Abstract
PESTalk is a novel method for generating 3D facial animations with personalized emotional styles directly from speech. It overcomes key limitations of existing approaches by introducing a Dual-Stream Emotion Extractor (DSEE) that captures both time and frequency-domain audio features for fine-grained emotion analysis, and an Emotional Style Modeling Module (ESMM) that models individual expression patterns based on voiceprint characteristics. To address data scarcity, the method leverages a newly constructed 3D-EmoStyle dataset. Evaluations demonstrate that PESTalk outperforms state-of-the-art methods in producing realistic and personalized facial animations.
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