Although lyrics generation has achieved significant progress in recent years, it has limited practical applications because the generated lyrics cannot be performed without composing compatible melodies. In this work, we bridge this practical gap by proposing a song rewriting system which rewrites the lyrics of an existing song such that the generated lyrics are compatible with the rhythm of the existing melody and thus singable. In particular, we propose SongRewriter, a controllable Chinese lyric generation and editing system which assists users without prior knowledge of melody composition. The system is trained by a randomized multi-level masking strategy which produces a unified model for generating entirely new lyrics or editing a few fragments. To improve the controllabiliy of the generation process, we further incorporate a keyword prompt to control the lexical choices of the content and propose novel decoding constraints and a vowel modeling task to enable flexible end and internal rhyme schemes. While prior rhyming metrics are mainly for rap lyrics, we propose three novel rhyming evaluation metrics for song lyrics. Both automatic and human evaluations show that the proposed model performs better than the state-of-the-art models in both contents and rhyming quality. Our code and models implemented in MindSpore Lite tool will be available.
翻译:虽然近年来歌词制作取得了显著进展,但实际应用有限,因为制作的歌词无法在没有兼容的旋律的情况下完成。在这项工作中,我们提出重写歌曲的歌词系统,以重写现有歌曲的歌词,使歌词与现有旋律的节奏相容,从而可以唱出。特别是,我们提出宋版Rewride,这是一个可控的中国歌词生成和编辑系统,它帮助没有事先了解旋律成份的用户。这个系统由随机化的多级别掩码战略来培训,它为制作全新歌词或编辑少数片段制作一个统一的模型。为了改进生成过程的控制拉比,我们进一步纳入一个关键词,以便控制内容的词汇选择,并提出新的解码限制和誓言建模任务,以促成灵活的结局和内部押韵计划。虽然先前的旋律计量仪主要用于歌词,但我们提议了三种新型的曲调评价指标,用于歌词歌词。两个自动和人类评价都显示,拟议的模型将比现在使用的思维质量模型中的状态模型更好。