EvalTalker: Learning to Evaluate Real-Portrait-Driven Multi-Subject Talking Humans

Yingjie Zhou; Xilei Zhu; Siyu Ren; Ziyi Zhao; Ziwen Wang; Farong Wen; Yu Zhou; Jiezhang Cao; Xiongkuo Min; Fengjiao Chen; Xiaoyu Li; Xuezhi Cao; Guangtao Zhai; Xiaohong Liu

arXiv · 2512.01340

EvalTalker: Learning to Evaluate Real-Portrait-Driven Multi-Subject Talking Humans

Yingjie Zhou·Xilei Zhu·Siyu Ren·Ziyi Zhao·Ziwen Wang·Farong Wen·Yu Zhou·Jiezhang Cao·Xiongkuo Min·Fengjiao Chen·Xiaoyu Li·Xuezhi Cao·Guangtao Zhai·Xiaohong Liu

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Abstract

Speech-driven Talking Human (TH) generation, commonly known as "Talker," currently faces limitations in multi-subject driving capabilities. Extending this paradigm to "Multi-Talker," capable of animating multiple subjects simultaneously, introduces richer interactivity and stronger immersion in audiovisual communication. However, current Multi-Talkers still exhibit noticeable quality degradation caused by technical limitations, resulting in suboptimal user experiences. To address this challenge, we construct THQA-MT, the first large-scale Multi-Talker-generated Talking Human Quality Assessment dataset, consisting of 5,492 Multi-Talker-generated THs (MTHs) from 15 representative Multi-Talkers using 400 real portraits collected online. Through subjective experiments, we analyze perceptual discrepancies among different Multi-Talkers and identify 12 common types of distortion. Furthermore, we introduce EvalTalker, a novel TH quality assessment framework. This framework possesses the ability to perceive global quality, human characteristics, and identity consistency, while integrating Qwen-Sync to perceive multimodal synchrony. Experimental results demonstrate that EvalTalker achieves superior correlation with subjective scores, providing a robust foundation for future research on high-quality Multi-Talker generation and evaluation.

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Yingjie Zhou, Xilei Zhu, Siyu Ren, Ziyi Zhao, Ziwen Wang, Farong Wen, Yu Zhou, Jiezhang Cao, Xiongkuo Min, Fengjiao Chen, Xiaoyu Li, Xuezhi Cao, Guangtao Zhai, Xiaohong Liu. 2025-12-01. EvalTalker: Learning to Evaluate Real-Portrait-Driven Multi-Subject Talking Humans. https://arxiv.org/abs/2512.01340

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