AI RESEARCH

Temporally-Aligned Evaluation for Audio-Driven Talking Head Generation

arXiv CS.AI

ArXi:2606.01031v1 Announce Type: cross Audio-driven talking-head generation has advanced rapidly, yet existing evaluation protocols mainly rely on frame-wise metrics that assume strict temporal correspondence between generated and reference videos. This assumption does not match speech-driven facial motion, which naturally includes slight timing shifts, different speaking speeds, and stylistic variations. As a result, conventional metrics may treat harmless timing differences as quality errors, making it harder to fairly compare methods and understand their trade-offs.