Summary of Agent-driven Large Language Models For Mandarin Lyric Generation, by Hong-hsiang Liu et al.
Agent-Driven Large Language Models for Mandarin Lyric Generation
by Hong-Hsiang Liu, Yi-Wen Liu
First submitted to arxiv on: 2 Oct 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The paper presents a multi-agent system that decomposes the melody-to-lyric task into sub-tasks, improving the quality of generated lyrics for tonal contour languages like Mandarin. The approach considers factors such as rhyme, syllable count, lyric-melody alignment, and consistency, and is validated by the Mpop600 dataset. Listening tests are conducted using a diffusion-based singing voice synthesizer to evaluate the quality of generated lyrics. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary The study developed a new way to create song lyrics that sound good with music. They used a special system with multiple agents working together to make sure the lyrics fit the melody and have the right rhythm, rhyme, and syllable count. The results were tested by people who listened to the synthesized singing voice and evaluated the quality of the generated lyrics. |
Keywords
» Artificial intelligence » Alignment » Diffusion
