Small Tunes Transformer: Exploring Macro & Micro-Level Hierarchies for Skeleton-Conditioned Melody Generation
Yishan Lv, Jing Luo, Boyuan Ju, Xinyu Yang

TL;DR
This paper introduces Small Tunes Transformer, a hierarchical music generation model that leverages macro and micro-level structures, including phrase segmentation and skeleton notes, to improve Chinese folk song melody synthesis.
Contribution
It proposes a novel hierarchical framework with phrase-level cross-attention and introduces a new Chinese folk music dataset for conditioned melody generation.
Findings
Outperforms state-of-the-art models in melody generation
Effective use of hierarchical structures improves musical coherence
New evaluation metrics for rhythm and melody quality
Abstract
Recently, symbolic music generation has become a focus of numerous deep learning research. Structure as an important part of music, contributes to improving the quality of music, and an increasing number of works start to study the hierarchical structure. In this study, we delve into the multi-level structures within music from macro-level and micro-level hierarchies. At the macro-level hierarchy, we conduct phrase segmentation algorithm to explore how phrases influence the overall development of music, and at the micro-level hierarchy, we design skeleton notes extraction strategy to explore how skeleton notes within each phrase guide the melody generation. Furthermore, we propose a novel Phrase-level Cross-Attention mechanism to capture the intrinsic relationship between macro-level hierarchy and micro-level hierarchy. Moreover, in response to the current lack of research on…
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Taxonomy
TopicsMusic and Audio Processing · Music Technology and Sound Studies · Speech and Audio Processing
