A unified graph neural network trained on heterogeneous symbolic music datasets achieves competitive multi-task music analysis with better cross-dataset robustness than single-corpus models.
Transactions of the International Society for Music Information Retrieval (TISMIR)3(1), 42–54 (2020)
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AnalysisGNN: Unified Music Analysis with Graph Neural Networks
A unified graph neural network trained on heterogeneous symbolic music datasets achieves competitive multi-task music analysis with better cross-dataset robustness than single-corpus models.