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

• URL: http://arxiv.org/abs/2411.13100v1
• Date: Wed, 20 Nov 2024 07:57:58 GMT
• Title: Song Form-aware Full-Song Text-to-Lyrics Generation with Multi-Level Granularity Syllable Count Control
• Authors: Yunkee Chae, Eunsik Shin, Hwang Suntae, Seungryeol Paik, Kyogu Lee,
• Abstract summary: We propose a framework for lyrics generation that enables multi-level syllable control at the word, phrase, line, and paragraph levels. Our approach generates complete lyrics conditioned on input text and song form, ensuring alignment with specified syllable constraints.
• Score: 13.702198736153582
• License:
• Abstract: 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

Related papers

• SongCreator: Lyrics-based Universal Song Generation [53.248473603201916]
  SongCreator is a song-generation system designed to tackle the challenge of generating songs with both vocals and accompaniment given lyrics. The model features two novel designs: a meticulously designed dual-sequence language model (M) to capture the information of vocals and accompaniment for song generation, and a series of attention mask strategies for DSLM. Experiments demonstrate the effectiveness of SongCreator by achieving state-of-the-art or competitive performances on all eight tasks.
  arXiv  Detail & Related papers  (2024-09-09T19:37:07Z)
• REFFLY: Melody-Constrained Lyrics Editing Model [50.03960548399128]
  We introduce REFFLY, the first revision framework designed to edit arbitrary forms of plain text draft into high-quality, full-fledged song lyrics. Our approach ensures that the generated lyrics retain the original meaning of the draft, align with the melody, and adhere to the desired song structures.
  arXiv  Detail & Related papers  (2024-08-30T23:22:34Z)
• Sudowoodo: a Chinese Lyric Imitation System with Source Lyrics [10.99860269567001]
  We introduce textbftextitSudowoodo, a Chinese lyrics imitation system that can generate new lyrics based on the text of source lyrics. During the inference process, we utilize a post-processing module to filter and rank the generated lyrics, selecting the highest-quality ones. The human evaluation results show that our framework can perform better lyric imitation.
  arXiv  Detail & Related papers  (2023-08-09T02:12:04Z)
• Unsupervised Melody-to-Lyric Generation [91.29447272400826]
  We propose a method for generating high-quality lyrics without training on any aligned melody-lyric data. We leverage the segmentation and rhythm alignment between melody and lyrics to compile the given melody into decoding constraints. Our model can generate high-quality lyrics that are more on-topic, singable, intelligible, and coherent than strong baselines.
  arXiv  Detail & Related papers  (2023-05-30T17:20:25Z)
• Unsupervised Melody-Guided Lyrics Generation [84.22469652275714]
  We propose to generate pleasantly listenable lyrics without training on melody-lyric aligned data. We leverage the crucial alignments between melody and lyrics and compile the given melody into constraints to guide the generation process.
  arXiv  Detail & Related papers  (2023-05-12T20:57:20Z)
• SongRewriter: A Chinese Song Rewriting System with Controllable Content and Rhyme Scheme [32.60994266892925]
  We propose a controllable Chinese lyrics 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.
  arXiv  Detail & Related papers  (2022-11-28T03:52:05Z)
• SongMASS: Automatic Song Writing with Pre-training and Alignment Constraint [54.012194728496155]
  SongMASS is proposed to overcome the challenges of lyric-to-melody generation and melody-to-lyric generation. It leverages masked sequence to sequence (MASS) pre-training and attention based alignment modeling. We show that SongMASS generates lyric and melody with significantly better quality than the baseline method.
  arXiv  Detail & Related papers  (2020-12-09T16:56:59Z)
• Melody-Conditioned Lyrics Generation with SeqGANs [81.2302502902865]
  We propose an end-to-end melody-conditioned lyrics generation system based on Sequence Generative Adversarial Networks (SeqGAN) We show that the input conditions have no negative impact on the evaluation metrics while enabling the network to produce more meaningful results.
  arXiv  Detail & Related papers  (2020-10-28T02:35:40Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.