Data-driven musical version identification: accuracy, scalability and bias perspectives 

Yesiler, M. Furkan (Date of defense: 2022-01-12)

This dissertation aims at developing audio-based musical version identification (VI) systems for industry-scale corpora. To employ such systems in industrial use cases, they must demonstrate high performance on large-scale ...