Katharina Prinz, Arthur Flexer, Gerhard Widmer,
"The Impact of Label Noise on a Music Tagger"
: Proceedings of the 13th International Workshop on Machine Learning and Music, European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2020, 8-2020
Original Titel:
The Impact of Label Noise on a Music Tagger
Sprache des Titels:
Englisch
Original Buchtitel:
Proceedings of the 13th International Workshop on Machine Learning and Music, European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2020
Original Kurzfassung:
We explore how much can be learned from noisy labels in au-
dio music tagging. Our experiments show that carefully annotated labels
result in highest figures of merit, but even high amounts of noisy labels
contain enough information for successful learning. Artificial corruption
of curated data allows us to quantize this contribution of noisy labels.