2024/08/19 by Yixiao Yuan, Yuan, Yixiao, Yangchen Huang +11 · 3 citations
Computer Science · #Advanced Computational Techniques and Applications #Art #Computational Physics and Python Applications #Computer science #Generator (circuit theory) #Literature #Physics #Poetry #Power (physics) #Rhyme #Video Analysis and Summarization
paper · pdf · doi:10.48550/arxiv.2408.10130
published in arXiv (Cornell University) (Cornell University)
openalex publication_date 2024/08/19 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
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.