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Multi-scale Fusion and Channel Weighted CNN for Acoustic Scene Classification by Yang, Liping ;Chen, Xinxing ;Tao, Lianjie ;Gu, Xiaohua is a scholarly article available to read on EtoBox.

What is Multi-scale Fusion and Channel Weighted CNN for Acoustic Scene Classification about?

Ensemble semantic features are useful for acoustic scene classification. In this paper, we proposed a multi-scale fusion and channel weighted CNN framework. The framework consists of two stages: the multi-scale feature fusion and channel weighting stages. The multi-scale feature fusion stage extracts hierarchy semantic feature maps using a CNN with simplified Xception architecture and then integrates multi-scale semantic features through a topdown pathway. The channel weighting stage squeezes feature maps into a channel descriptor and then transforms it into a set of channel weighting factors to reinforce the importance of each channel for acoustic scene classification. Experimental results on DCASE2018 acoustic scene classification subtask A and subtask B demonstrate the performances of the proposed framework.

Author

Yang, Liping ;Chen, Xinxing ;Tao, Lianjie ;Gu, Xiaohua

Publisher

ACM

Published

2019

Language

EN