Tootfinder

Benchmarking Music Autotagging with MGPHot Expert Annotations vs. Generic Tag Datasets
Pedro Ramoneda, Pablo Alonso-Jimenez, Sergio Oramas, Xavier Serra, Dmitry Bogdanov
https://arxiv.org/abs/2509.06936

Benchmarking Music Autotagging with MGPHot Expert Annotations vs. Generic Tag Datasets
Music autotagging aims to automatically assign descriptive tags, such as genre, mood, or instrumentation, to audio recordings. Due to its challenges, diversity of semantic descriptions, and practical value in various applications, it has become a common downstream task for evaluating the performance of general-purpose music representations learned from audio data. We introduce a new benchmarking dataset based on the recently published MGPHot dataset, which includes expert musicological annotati…