Song translation requires both translation of lyrics and alignment of music
notes so that the resulting verse can be sung to the accompanying melody, which
is a challenging problem that has attracted some interests in different aspects
of the translation process. In this paper, we propose Lyrics-Melody Translation
with Adaptive Grouping (LTAG), a holistic solution to automatic song
translation by jointly modeling lyrics translation and lyrics-melody alignment.
It is a novel encoder-decoder framework that can simultaneously translate the
source lyrics and determine the number of aligned notes at each decoding step
through an adaptive note grouping module. To address data scarcity, we
commissioned a small amount of training data annotated specifically for this
task and used large amounts of augmented data through back-translation.
Experiments conducted on an English-Chinese song translation data set show the
effectiveness of our model in both automatic and human evaluation.

本文提出了一种新颖的编码器 - 解码器框架 ——Lyrics-Melody Translation with Adaptive Grouping (LTAG)，通过自适应音符分组模块，可以同时翻译源歌词并确定每个解码步骤中对齐音符的数量，通过注释数据和后翻译使用大量的增广数据，实现了自动歌曲翻译的完整解决方案，并在英汉歌曲翻译数据集上进行实验，结果表明模型在自动和人类评估中均有效。