论文标题
标签噪声对音乐标记器的影响
The Impact of Label Noise on a Music Tagger
论文作者
论文摘要
我们探索从音频音乐标记中的嘈杂标签中可以学到多少。我们的实验表明，精心注释的标签可产生最高功绩，但即使是大量的嘈杂标签也包含足够的信息以成功学习。精选数据的人工损坏使我们能够量化嘈杂标签的这种贡献。
We explore how much can be learned from noisy labels in audio 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.
