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Deep neural networks (DNNs) have recently achieved great success in amultitude of classification tasks. Ensembles of DNNs have been shown to improvethe performance. In this paper, we explore the recent state-of-the-art DNNsused for image classification. We modified these DNNs and applied them to thetask of acoustic scene classification. We conducted a number of experiments onthe TUT Acoustic Scenes 2017 dataset to empirically compare these methods.Finally, we show that the best model improves the baseline score for DCASE-2017Task 1 by 3.1% in the test set and by 10% in the development set.

Ensemble Of Deep Neural Networks For Acoustic Scene Classification