In the realm of media technology, digital humans have gained prominence due
to rapid advancements in computer technology. However, the manual modeling and
control required for the majority of digital humans pose significant obstacles
to efficient development. The speech-driven methods offer a novel avenue for
manipulating the mouth shape and expressions of digital humans. Despite the
proliferation of driving methods, the quality of many generated talking head
(TH) videos remains a concern, impacting user visual experiences. To tackle
this issue, this paper introduces the Talking Head Quality Assessment (THQA)
database, featuring 800 TH videos generated through 8 diverse speech-driven
methods. Extensive experiments affirm the THQA database's richness in character
and speech features. Subsequent subjective quality assessment experiments
analyze correlations between scoring results and speech-driven methods, ages,
and genders. In addition, experimental results show that mainstream image and
video quality assessment methods have limitations for the THQA database,
underscoring the imperative for further research to enhance TH video quality
assessment. The THQA database is publicly accessible at
this https URL

本文介绍了 Talking Head Quality Assessment（THQA）数据库，包括通过 8 种不同的语音驱动方法生成的 800 个 Talking Head 视频。通过大量实验表明了 THQA 数据库在角色和语音特征方面的丰富性。进一步的主观质量评估实验分析了评分结果与语音驱动方法、年龄和性别之间的相关性。实验结果还显示主流图像和视频质量评估方法在 THQA 数据库上存在局限性，强调了进一步研究以提高 TH 视频质量评估的迫切性。