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.

本文提出了一种可控的中文歌词生成和编辑系统 SongRewriter，使用随机化的多级掩码策略进行训练，包括新歌词生成和现有歌词片段编辑，加入关键词提示和新的解码约束，提高了词汇选择的控制性以及末韵和内韵方案的灵活性。同时，提出了三个新的歌词押韵评估度量标准，并通过自动和人工评估表明，该模型在内容和韵律质量方面优于现有模型。