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Urban acoustic classification based on deep feature transfer learning
Shen,Yexin1,2; Cao,Jiuwen1,2; Wang,Jianzhong1,2; Yang,Zhixin3
Source PublicationJournal of the Franklin Institute

Urban acoustic classification (UAC) plays a vital role in smart city engineering, urban security, noise pollution analysis, etc. Convolutional neural networks (CNNs) based feature transfer learning have been shown competitive performance in many applications but little attention has been paid to UAC. In this study, a novel UAC algorithm exploiting the deep CNNs based feature transfer learning and the deep belief net (DBN) based classification is developed. The spectrogram is first adopted for the urban acoustic stream representation. Then, three deep CNNs pre-trained on ImageNet database are applied as feature extractors. The extracted features are concatenated and fed to a DBN for classifier learning. To achieve a good generalization performance, three restricted boltzmann machines (RBM) trained by the contrastive divergence algorithm (CD) followed by a back-propagation (BP) based fine parameter tuning is adopted in DBN. The proposed UAC is evaluated on a real acoustic database, including 11 categories of acoustic signals recorded from the urban environment. Performance comparisons to many state-of-the-art algorithms are presented to demonstrate the superiority of the proposed method.

URLView the original
Indexed BySCIE
WOS Research AreaAutomation & Control Systems ; Engineering ; Mathematics
WOS SubjectAutomation & Control Systems ; Engineering, Multidisciplinary ; Engineering, Electrical & Electronic ; Mathematics, Interdisciplinary Applications
WOS IDWOS:000507992000032
Scopus ID2-s2.0-85076003226
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Cited Times [WOS]:5   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
CollectionUniversity of Macau
Corresponding AuthorCao,Jiuwen
Affiliation1.Key Lab for IOT and Information Fusion Technology of Zhejiang,Hangzhou Dianzi University,Zhejiang,310018,China
2.Artificial Intelligence Institute,Hangzhou Dianzi University,Zhejiang,310018,China
3.State Key Laboratory of Internet of Things for Smart City,Faculty of Science and Technology,University of Macau,Macau,China
Recommended Citation
GB/T 7714
Shen,Yexin,Cao,Jiuwen,Wang,Jianzhong,et al. Urban acoustic classification based on deep feature transfer learning[J]. Journal of the Franklin Institute,2020,357(1):667-686.
APA Shen,Yexin,Cao,Jiuwen,Wang,Jianzhong,&Yang,Zhixin.(2020).Urban acoustic classification based on deep feature transfer learning.Journal of the Franklin Institute,357(1),667-686.
MLA Shen,Yexin,et al."Urban acoustic classification based on deep feature transfer learning".Journal of the Franklin Institute 357.1(2020):667-686.
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