论文标题
音调语言的自动歌曲翻译
Automatic Song Translation for Tonal Languages
论文作者
论文摘要
本文为音调语言开发了自动歌曲翻译（AST），并解决了单词的音调与歌曲的旋律相结合的独特挑战，这些挑战除了传达了原始含义。我们提出了有效AST的三个标准 - 保留含义，可唱性和清晰度 - 以及针对这些标准的设计指标。我们为英语歌曲翻译开发了一个新的基准测试，并开发了无监督的AST系统，自动歌曲翻译（Gagast）的指导对准（Gagast），该系统将预训练与三个解码约束结合在一起。自动评估和人类评估都表明，Gagast成功平衡了语义和单词。
This paper develops automatic song translation (AST) for tonal languages and addresses the unique challenge of aligning words' tones with melody of a song in addition to conveying the original meaning. We propose three criteria for effective AST -- preserving meaning, singability and intelligibility -- and design metrics for these criteria. We develop a new benchmark for English--Mandarin song translation and develop an unsupervised AST system, Guided AliGnment for Automatic Song Translation (GagaST), which combines pre-training with three decoding constraints. Both automatic and human evaluations show GagaST successfully balances semantics and singability.
