Lyric translation plays a pivotal role in amplifying the global resonance of
music, bridging cultural divides, and fostering universal connections.
Translating lyrics, unlike conventional translation tasks, requires a delicate
balance between singability and semantics. In this paper, we present a
computational framework for the quantitative evaluation of singable lyric
translation, which seamlessly integrates musical, linguistic, and cultural
dimensions of lyrics. Our comprehensive framework consists of four metrics that
measure syllable count distance, phoneme repetition similarity, musical
structure distance, and semantic similarity. To substantiate the efficacy of
our framework, we collected a singable lyrics dataset, which precisely aligns
English, Japanese, and Korean lyrics on a line-by-line and section-by-section
basis, and conducted a comparative analysis between singable and non-singable
lyrics. Our multidisciplinary approach provides insights into the key
components that underlie the art of lyric translation and establishes a solid
groundwork for the future of computational lyric translation assessment.

本文介绍了一个计算框架，旨在定量评估可唱译歌词，该框架无缝地融合了歌曲、语言和文化维度；通过收集一个可唱歌词数据集，并进行可唱和不可唱歌词的比较分析，我们验证了我们框架的有效性；我们的多学科方法揭示了歌曲翻译艺术的关键因素，并为未来的计算歌词翻译评估奠定了坚实基础。