mlsanityData to 14 Oct 2026

Song Form-aware Full-Song Text-to-Lyrics Generation with Multi-Level Granularity Syllable Count Control

arXiv 2411.13100 ↗First posted 20 Nov 2024cs.CL cs.AIcited by 1

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Abstract (arXiv)

Lyrics generation presents unique challenges, particularly in achieving precise syllable control while adhering to song form structures such as verses and choruses. Conventional line-by-line approaches often lead to unnatural phrasing, underscoring the need for more granular syllable management. We propose a framework for lyrics generation that enables multi-level syllable control at the word, phrase, line, and paragraph levels, aware of song form. Our approach generates complete lyrics conditioned on input text and song form, ensuring alignment with specified syllable constraints. Generated lyrics samples are available at: https://tinyurl.com/lyrics9999

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 26 of its 46 references that are in the map. First posted on arXiv 20 Nov 2024.

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26 of 46 references.

References · 26

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14 more
  1. 2023Evaluating Large Language Models on Controlled Generation Taskscited by 73
  2. 2020SongMASS: Automatic Song Writing with Pre-training and Alignment Constraintcited by 41
  3. 2019Conditional LSTM-GAN for Melody Generation from Lyricscited by 31
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  6. 2020Melody-Conditioned Lyrics Generation with SeqGANscited by 14
  7. 2022Automatic Song Translation for Tonal Languagescited by 12
  8. 2023Contrastive Learning-Based Audio to Lyrics Alignment for Multiple Languagescited by 11
  9. 2023Unsupervised Melody-to-Lyric Generationcited by 7
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  14. 2023Syllable-level lyrics generation from melody exploiting character-level language modelcited by 2

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 1.

1 paper.

  1. 2026CoLyricist: Enhancing Lyric Writing with AI through Workflow-Aligned Supportcited by 1