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.
@article{arxiv.2408.10130,
title = {Rhyme-aware Chinese lyric generator based on GPT},
author = {Yixiao Yuan and Yangchen Huang and Yu Ma and Xinjin Li and Zhenglin Li and Yiming Shi and Huapeng Zhou},
journal= {arXiv preprint arXiv:2408.10130},
year = {2024}
}