arXiv:2503.14295v3 Announce Type: replace-cross Abstract: Recent advancements in audio-driven talking face generation have made great progress in lip synchronization. However, current methods often lack sufficient control over facial animation such as speaking style and emotional expression, resulting in uniform outputs. In this paper, we focus on improving two key factors: lip-audio alignment and emotion control, to enhance the diversity and user-friendliness of talking videos. Lip-audio alignment control focuses on elements like speaking style and the scale of lip movements, whereas emotion
Advances in AI, particularly in generative models and computer vision, are enabling more precise control over complex outputs like facial animation, pushing the boundaries of realistic digital interaction.
Improved control over AI-generated facial animations, including style and emotion, enhances the utility and realism of digital humans, virtual assistants, and media production, impacting diverse industries.
Talking face generation is moving beyond basic lip synchronization to nuanced emotional and stylistic expression, allowing for more engaging and customizable AI-driven communications.
- · Digital content creators
- · Metaverse developers
- · Marketing and advertising industries
- · AI avatar companies
- · Companies offering rudimentary talking avatar services
- · Traditional animation studios reliant on manual facial rigging
- · Deepfake detection technologies (initially, due to increased realism)
More realistic and expressive AI-generated talking faces become commonplace in virtual interactions and media.
The demand for emotional and stylistic control in AI systems increases, driving further research and development in affective computing.
The line between synthetic and real human interaction blurs further, potentially leading to new forms of communication, entertainment, and identity challenges.
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Read at arXiv cs.AI