Rhyme-aware Chinese lyric generator based on GPT
Neural language representation models such as GPT, pre-trained on large-scale corpora, can effectively capture rich semantic patterns from plain text and be fine-tuned to consistently improve natural language generation performance. However, existing pre-trained language models used to generate lyrics rarely consider rhyme information, which is crucial in lyrics. Using a pre-trained model directly results in poor performance. To enhance the rhyming quality of generated lyrics, we incorporate integrated rhyme information into our model, thereby improving lyric generation performance.
Authors
- Yiming Shi
- Xinjin Li (ORCID: https://orcid.org/0000-0002-8406-4372)
- Yixiao Yuan
- Yu Ma (ORCID: https://orcid.org/0000-0003-3731-2764)
- Zhenglin Li (ORCID: https://orcid.org/0000-0003-0786-1068)
- Yangchen Huang
- Huapeng Zhou
Institutions
- University of Washington (US)
- Xi’an Jiaotong-Liverpool University (CN)
- Carnegie Mellon University (US)
- Columbia University (US)
- Texas A&M University (US)
Publication Details
- Published
- 2024-11-08
- DOI
- https://doi.org/10.1117/12.3049486
- Citations
- 15
- Primary Topic
- Computational Physics and Python Applications
- Type
- article
- Field-Weighted Citation Impact
- 5.21