论文标题
实践中的配音：对人类本地化的大规模研究，具有自动配音的见解
Dubbing in Practice: A Large Scale Study of Human Localization With Insights for Automatic Dubbing
论文作者
论文摘要
我们调查了人类如何执行将视频内容从一种语言配音为另一种语言的任务，以利用来自54个专业制作的标题的319.57小时视频的新型语料库。这是我们知道的第一项大规模研究。结果挑战了许多关于人配音和机器学习文献的定性文献中通常做出的许多假设，这些假设与普遍强调的等级（角色长度）和唇部合成约束的普遍性和翻译质量的重要性，以及对等距（Timing）约束的重要性的重要性。我们还通过翻译单词以外的其他渠道发现了源端音频对人配音的重大影响，这表明需要研究保留语音特征的方法，以及在自动配音系统中的语义转移，例如强调/情感。
We investigate how humans perform the task of dubbing video content from one language into another, leveraging a novel corpus of 319.57 hours of video from 54 professionally produced titles. This is the first such large-scale study we are aware of. The results challenge a number of assumptions commonly made in both qualitative literature on human dubbing and machine-learning literature on automatic dubbing, arguing for the importance of vocal naturalness and translation quality over commonly emphasized isometric (character length) and lip-sync constraints, and for a more qualified view of the importance of isochronic (timing) constraints. We also find substantial influence of the source-side audio on human dubs through channels other than the words of the translation, pointing to the need for research on ways to preserve speech characteristics, as well as semantic transfer such as emphasis/emotion, in automatic dubbing systems.
