Challenge: Pre-trained language models specifically designed at the syllable level are not available.
Approach: They propose to exploit character-level language models for syllable-level lyrics generation from symbolic melody.
Outcome: The proposed system improves coherence and correctness of generated lyrics without training expensive language models.

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A Melody-Conditioned Lyrics Language Model (N18-1)

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Challenge: Existing models for lyrics generation are insufficient to capture relationship between lyrics and melody.
Approach: They propose a data-driven language model that generates entire lyrics for a given melody.
Outcome: The proposed model generates fluent lyrics while maintaining compatibility between lyrics and melodies.
Unsupervised Melody-to-Lyrics Generation (2023.acl-long)

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Challenge: Existing methods for automatic melody-to-lyric generation are limited due to the limited amount of melody-lyrical aligned data.
Approach: They propose a method for automatic melody-to-lyric generation without training on any aligned melody-lyr data.
Outcome: The proposed model generates high-quality lyrics that are singable, intelligible, and coherent than baseline models.
SongComposer: A Large Language Model for Lyric and Melody Generation in Song Composition (2025.acl-long)

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Challenge: Creating lyrics and melodies in symbolic format requires expert knowledge of melody and an advanced understanding of lyrics.
Approach: They introduce SongComposer, a music-specialized large language model that can create symbolic lyrics and melodies following instructions.
Outcome: The proposed model outperforms existing models in symbolic song composition tasks.
Scansion-based Lyrics Generation (2024.lrec-main)

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Challenge: a new method for generating lyrics for Mandarin songs is based on scansion . the number of syllables required is variable due to the number and number of notes .
Approach: They propose a method to generate Mandarin lyrics with a good match between melody and tonal contour.
Outcome: The proposed system outperforms all other systems in lyric-melody fit and uses proxies for quantifying creativity.
DeepRapper: Neural Rap Generation with Rhyme and Rhythm Modeling (2021.acl-long)

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Challenge: Existing systems for rap generation focus on rhyming lyrics but ignore rhythmic beats . rap lyrics need to be semantically meaningful and fashionable to convey interesting stories .
Approach: They develop a Transformer-based rap generation system that can model both rhymes and rhythms.
Outcome: The proposed system generates high-quality raps with rhymes and rhythms . it is based on a Transformer-based language model .
QiuNiu: A Chinese Lyrics Generation System with Passage-Level Input (2022.acl-demo)

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Challenge: Existing systems based on attributes or keywords render lyrics generation very limited . previous studies focused on generating lyrics based only on attributes and keywords .
Approach: They propose to use Chinese passage-level text as input for lyrics generation . they initialize parameters with custom pretrained Chinese GPT-2 model and adopt a two-step process to fine-tune the model for better alignment between passage- level text and lyrics.
Outcome: The proposed system is conditioned on passage-level text rather than attributes or keywords, rendering limited control over the content of the lyrics.
Automatic Poetry Generation from Prosaic Text (2020.acl-main)

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Challenge: In recent years, successful approaches have emerged to accurately model various aspects of natural language.
Approach: They propose to combine neural networks with a poetry generation system that only uses standard text as input . they use standard text to model syntactic well-formedness and topical coherence .
Outcome: The proposed framework is applied to the generation of poems in English and French . it uses standard, non-poetic text and its output is constrained to confer a poetic character .
SongRewriter: A Chinese Song Rewriting System with Controllable Content and Rhyme Scheme (2023.findings-acl)

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Challenge: Existing methods of generating singable lyrics are based on a given melody, but there are two main challenges: generating the lyrics without knowing the melody and composing compatible melodies.
Approach: They propose a Chinese lyric generation and editing system which rewrites lyrics of an existing song such that they are compatible with the rhythm of the existing melody.
Outcome: The proposed system is based on a randomized multi-level masking strategy and can generate new lyrics or edit fragments without prior knowledge of melody composition.
ToneCraft: Cantonese Lyrics Generation with Harmony of Tones and Pitches (2025.emnlp-main)

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Challenge: Current research has not addressed the challenge of generating harmonious Cantonese lyrics.
Approach: They propose a framework for generating Cantonese lyrics that ensures tonal and melodic harmony.
Outcome: The proposed framework ensures tonal and melodic harmony while preserving character count and quality.
Sudowoodo: A Chinese Lyric Imitation System with Source Lyrics (2023.emnlp-demo)

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Challenge: Existing studies on lyrics generation focus on generating accurate lyrics using keywords, rhymes, etc. However, there is no parallel corpus for lyrics imitation.
Approach: They propose a Chinese lyrics imitation system that can generate new lyrics based on source lyrics.
Outcome: The proposed system can generate new lyrics based on the source lyrics . human evaluation shows it can perform better lyric imitation.

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