Summary of Rhyme-aware Chinese Lyric Generator Based on Gpt, by Yixiao Yuan et al.
Rhyme-aware Chinese lyric generator based on GPT
by Yixiao Yuan, Yangchen Huang, Yu Ma, Xinjin Li, Zhenglin Li, Yiming Shi, Huapeng Zhou
First submitted to arxiv on: 19 Aug 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 A neural language representation model like GPT, trained on massive datasets and fine-tuned for natural language generation, can excel at capturing semantic patterns in plain text. While these models are often used to generate lyrics, they typically disregard rhyme information, which is essential for creating engaging lyrics. To overcome this limitation, researchers propose incorporating rhyme data into the model’s training process, ultimately enhancing the quality of generated lyrics. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper trains a neural language representation model like GPT on massive datasets and fine-tunes it for natural language generation. The model captures rich semantic patterns from plain text and can improve performance when generating natural language. However, existing models used to generate lyrics don’t consider rhyme information, which is crucial for creating engaging lyrics. |
Keywords
* Artificial intelligence * Gpt
