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What is Chord Label Relationships in ACE Models about?

This paper discusses the use of musical relationships between chord labels to enhance Automatic Chord Extraction (ACE) tasks. It critiques existing ACE models for neglecting the inherent relationships between chords and proposes new training losses based on musical theory to improve the performance of Convolutional Neural Networks in ACE. The authors also introduce novel chord distances and a tailored analysis method to better understand classification errors in ACE systems.

Author

Savvas Vagenas

Language

EN