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.

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Challenge: Existing models for lyrics generation are insufficient to capture relationship between lyrics and melody.
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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.
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Challenge: Pre-trained language models specifically designed at the syllable level are not available.
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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.
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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 .
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Challenge: Song translation requires both translation of lyrics and alignment of music notes . human translators of songs need to have a mastery of cultural traditions and the poetic usage of both source and target languages .
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REFFLY: Melody-Constrained Lyrics Editing Model (2025.naacl-long)

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Challenge: Automatic melody-to-lyric (M2L) generation aims to create lyrics that align with a given melody.
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Challenge: Current research has not addressed the challenge of generating harmonious Cantonese lyrics.
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iComposer: An Automatic Songwriting System for Chinese Popular Music (N19-4)

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Challenge: iComposer is an interactive web-based songwriting system designed to assist human creators by greatly simplifying music production.
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Generative Music Models’ Alignment with Professional and Amateur Users’ Expectations (2025.findings-acl)

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Challenge: Recent years have witnessed rapid advances in text-to-music generation using large language models.
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