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This technical report describes the IOA team's submission for TASK1A ofDCASE2019 challenge. Our acoustic scene classification (ASC) system adopts adata augmentation scheme employing generative adversary networks. Two majorclassifiers, 1D deep convolutional neural network integrated with scalogramfeatures and 2D fully convolutional neural network integrated with Mel filterbank features, are deployed in the scheme. Other approaches, such as adversarycity adaptation, temporal module based on discrete cosine transform and hybridarchitectures, have been developed for further fusion. The results of ourexperiments indicates that the final fusion systems A-D could achieve anaccuracy higher than 85% on the officially provided fold 1 evaluation dataset.

Integrating the Data Augmentation Scheme with Various Classifiers for Acoustic Scene Modeling