Classification of UrbanSound8k: A Study Using Convolutional Neural Network and Multiple Data Augmentation Techniques-Reference-Cited by-同舟云学术

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Classification of UrbanSound8k: A Study Using Convolutional Neural Network and Multiple Data Augmentation Techniques

Published:2021 Issue: Volume: Page:52-64
ISSN:1865-0929
Container-title:Soft Computing and its Engineering Applications
language:
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Author:

Rahman Aamer Abdul^ORCID,Angel Arul Jothi J.^ORCID

Publisher

Springer Singapore

Link

https://link.springer.com/content/pdf/10.1007/978-981-16-0708-0_5

Reference15 articles.

1. Stansfeld, S., Matheson, M.: Noise pollution: non-auditory effects on health. Br. Med. Bull. 68, 243–257 (2003). https://doi.org/10.1093/bmb/ldg033

2. Salamon, J., Jacoby, C., Bello, J.P.: A dataset and taxonomy for urban sound research. In: Proceedings of the ACM International Conference on Multimedia, MM 2014 (2014). https://doi.org/10.1145/2647868.2655045

3. Piczak, K.J.: Environmental sound classification with convolutional neural networks. In: IEEE 25th International Workshop on Machine Learning for Signal Processing (MLSP) (2015). https://doi.org/10.1109/mlsp.2015.7324337

4. Salamon, J., Bello, J.P.: Deep convolutional neural networks and data augmentation for environmental sound classification. IEEE Signal Process. Lett. 24(3), 279–283 (2017). https://doi.org/10.1109/lsp.2017.2657381

5. Sang, J., Park, S., Lee, J.: Convolutional recurrent neural networks for urban sound classification using raw waveforms. In: 2018 26th European Signal Processing Conference (EUSIPCO) (2018). https://doi.org/10.23919/eusipco.2018.8553247

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