Ensemble Of Deep Neural Networks For Acoustic Scene Classification

2017/08/19 by Venkatesh Duppada, Duppada, Venkatesh, Sushant Hiray +1
Computer Science · #FOS: Computer and information sciences #Music Technology and Sound Studies #Music and Audio Processing #Sound (cs.SD) #Speech and Audio Processing #cs.SD

paper · pdf · doi:10.48550/arxiv.1708.05826

Detection and Classification of Acoustic Scenes and Events 2017

openalex publication_date 2017/08/19 · arxiv created 2017/10/03 · arxiv updated 2017/10/04 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

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

Citations

• ADADELTA: An Adaptive Learning Rate Method

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