Attention and Localization Based on a Deep Convolutional Recurrent Model for Weakly Supervised Audio Tagging

@inproceedings{Xu2017AttentionAL,
  title={Attention and Localization Based on a Deep Convolutional Recurrent Model for Weakly Supervised Audio Tagging},
  author={Yong Xu and Qiuqiang Kong and Qiang Huang and Wenwu Wang and Mark D. Plumbley},
  booktitle={INTERSPEECH},
  year={2017}
}
Audio tagging aims to perform multi-label classification on audio chunks and it is a newly proposed task in the Detection and Classification of Acoustic Scenes and Events 2016 (DCASE 2016) challenge. This task encourages research efforts to better analyze and understand the content of the huge amounts of audio data on the web. The difficulty in audio tagging is that it only has a chunk-level label without a frame-level label. This paper presents a weakly supervised method to not only… 

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