Asymmetric kernel convolutional neural network for acoustic scenes classification

Chien Yao Wang, Jia Ching Wang, Yu Chi Wu, Pao Chi Chang

研究成果: 書貢獻/報告類型會議論文篇章同行評審

1 引文 斯高帕斯(Scopus)

摘要

In this Zwork, Zwe propose an Asymmetric Kernel Convolutional Neural NetZwork (AKCNN) for Acoustic Scenes Classification (ASC). Its kernel shape is not the traditional square but asymmetric in Zwidth and height. It also uses Weight Normalization (WN) to accelerate the training process because it can early converge the training loss and accuracy. The best of all, WN can help increase the accuracy of ASC. TUT Acoustic Scenes 2016 Dataset [1] is used for evaluation. The result shoZws that AKCNN achieves accuracy 86.7%. If Zwe rank the score in DCASE2016 ASC Challenge, it shoZws that the system Zwould have a higher score than the 5th place.

原文???core.languages.en_GB???
主出版物標題2017 IEEE International Symposium on Consumer Electronics, ISCE 2017
發行者Institute of Electrical and Electronics Engineers Inc.
頁面11-12
頁數2
ISBN(電子)9781538654330
出版狀態已出版 - 4 5月 2018
事件21st IEEE International Symposium on Consumer Electronics, ISCE 2017 - Kuala Lumpur, Malaysia
持續時間: 14 11月 201715 11月 2017

出版系列

名字Proceedings of the International Symposium on Consumer Electronics, ISCE

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???event.eventtypes.event.conference???21st IEEE International Symposium on Consumer Electronics, ISCE 2017
國家/地區Malaysia
城市Kuala Lumpur
期間14/11/1715/11/17

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