Generating Gezi Opera Scores with a Large Language Model and a High-Quality Dataset

Abstract

Despite significant progress in music generation technology recently, covering various unique styles and genres, the generation of Chinese opera scores still urgently requires more attention, primarily due to the lack of a high-quality and lyric-melody alignment opera score dataset. In this study, we collect pictures of the jianpu of the Chinese Gezi opera and manually construct a high-quality standard data set of Chinese Gezi opera scores, which can be read by music notation software. This dataset includes 142 lyric-melody alignment Gezi opera scores, and it is intended to facilitate opera score generation and analysis. In the lyric-to-melody generation task, we design a triple data format (lyric, notes, and note lengths) specifically for Gezi opera scores. This data format aligns lyric and melody aims to enhance the model’s understanding and generation capabilities. Experiments show that our designed data format exhibits superior performance in the Gezi opera lyric-to-melody generation task, significantly outperforming strong baseline methods. Specifically, it surpasses the state-of-the-art model by 5. 04% in pitch distribution similarity, improves duration distribution similarity by 8. 62%, and achieves a lower melody distance of 0.49. Download information can be found at https://github.com/ZhenLEI96/GeziOperaDataset.