Audio Tagging by Cross Filtering Noisy Labels

@article{Zhu2020AudioTB,
  title={Audio Tagging by Cross Filtering Noisy Labels},
  author={Boqing Zhu and Kele Xu and Qiuqiang Kong and Huaimin Wang and Yuxing Peng},
  journal={IEEE/ACM Transactions on Audio, Speech, and Language Processing},
  year={2020},
  volume={28},
  pages={2073-2083}
}
  • Boqing Zhu, Kele Xu, Yuxing Peng
  • Published 16 July 2020
  • Computer Science
  • IEEE/ACM Transactions on Audio, Speech, and Language Processing
High quality labeled datasets have allowed deep learning to achieve impressive results on many sound analysis tasks. Yet, it is labor-intensive to accurately annotate large amount of audio data, and the dataset may contain noisy labels in the practical settings. Meanwhile, the deep neural networks are susceptive to those incorrect labeled data because of their outstanding memorization ability. In this article, we present a novel framework, named CrossFilter, to combat the noisy labels problem… 
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