Music has a unique and complex structure which is challenging for both expert humans and
existing AI systems to understand, and presents unique challenges relative to other forms of …

This editorial introduces the new education track for the Transactions of the International
Society for Music Information Retrieval (TISMIR) and aims to provide guidance to both …

Version identification (VI) has seen substantial progress over the past few years. On the one
hand, the introduction of the metric learning paradigm has favored the emergence of …

In the past decades, convolutional neural networks (CNNs) have been commonly adopted in
audio perception tasks, which aim to learn latent representations. However, for audio …

Computing music similarity is an indispensable component in developing music search
service. This paper proposes a relevance weight of each chromagram vector for cover song …

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 …

Computing music similarity is an indispensable component in developing music search
service. This paper focuses on learning a music similarity function in order to boost cover …