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PVSync: A Unified Lip-Sync Expert for Timing and Articulation
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Kevin Stephen, Varun Menon, Timo Mertens, Nikita Drobyshev

· 1 min read

ResearcharXiv cs.CV

PVSync: A Unified Lip-Sync Expert for Timing and Articulation

arXiv:2610.09223v1 Announce Type: new Abstract: Lip movements can match the timing of speech without matching the spoken sounds. We introduce PVSync, a unified model for audio-visual offset estimation and phoneme-level articulation scoring. PVSync combines window-level contrastive learning for synchronisation with a phoneme-level articulation objective that aligns audio and video embeddings of the same viseme class across clips. Visemes group phonemes with similar visible articulation. Viseme labels are derived automatically from forced-aligned transcripts, without manual annotations. On offset-corrected videos from 13 talking-head video generation models, PVSync matches human rankings of lip-sync quality more closely than LSE-C, achieving a Spearman correlation of 0.83 versus 0.34. On an automatically constructed benchmark from held-out speech, PVSync distinguishes viseme-matched from mismatched audio-visual pairs with an ROC AUC of 0.91. PVSync also outperforms SyncNet and MTD-VocaLiST in temporal offset recovery on held-out in-the-wild clips. Code and benchmark data will be released upon acceptance.

Original source

This story was published by arXiv cs.CV and written by Kevin Stephen, Varun Menon, Timo Mertens, Nikita Drobyshev. SyncAI.news shows a preview; the complete article is on the publisher's site.

Read the full story on arxiv.org

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