Word Representation for Rhythms
This work addresses the challenge of systematically analyzing musical rhythms for researchers in music information retrieval, though it appears incremental in applying existing NLP methods to rhythm data.
The paper tackles the problem of representing musical rhythms by proposing a word representation strategy that creates a 450-word rhythm dictionary from 1,034 pieces in the Nottingham Dataset, and uses a BERT model to analyze rhythm syntax, enabling the identification of music structures and meter clustering.
This paper proposes a word representation strategy for rhythm patterns. Using 1034 pieces of Nottingham Dataset, a rhythm word dictionary whose size is 450 (without control tokens) is generated. BERT model is created to explore syntactic potentials of rhythm words. Our model is able to find overall music structures and cluster different meters. In a larger scheme, a think mode - music as language - is proposed for systematic considerations.