Abstract
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.
Abstract (translated)
在媒体技术领域，数字人因计算机技术的快速发展而取得了突出地位。然而，大多数数字人所需的手动建模和控制对高效开发造成了巨大的障碍。语音驱动的方法为操纵数字人的嘴形状和表情提供了一个新颖的途径。尽管驱动方法的普及，但许多生成的交谈头（TH）视频的质量仍然令人担忧，影响了用户的视觉体验。为解决这个问题，本文介绍了 Talking Head Quality Assessment (THQA) 数据库，该数据库通过8种不同的语音驱动方法生成了800个TH视频。广泛的实验证实了THQA数据库的角色和语音特征的丰富性。后续的主观质量评估实验分析了评分结果与语音驱动方法、年龄和性别的相关性。此外，实验结果表明，主流图像和视频质量评估方法对THQA数据库存在局限性，进一步研究以提高TH视频质量评估的必要性。THQA数据库现在可以在此链接公开访问：https://www.THQA-db.com/
URL
https://arxiv.org/abs/2404.09003
