Convolutional Neural Networks in Speech Emotion Recognition – Time-Domain and Spectrogram-Based Approach

Author:

Stasiak Bartłomiej,Opałka Sławomir,Szajerman Dominik,Wojciechowski Adam

Publisher

Springer International Publishing

Reference20 articles.

1. Dean, J., Patterson, D., Young, C.: A new golden age in computer architecture: empowering the machine-learning revolution. IEEE Micro 38(2) (2018)

2. Krizhevsky, A., Sutskever, I., Hinton, G.E.: Imagenet classification with deep convolutional neural networks. In: Pereira, F., Burges, C.J.C., Bottou, L., Weinberger, K.Q. (eds.) Advances in Neural Information Processing Systems 25, pp. 1097–1105. Curran Associates Inc. (2012)

3. Opałka, S., Stasiak, B., Szajerman, D., Wojciechowski, A.: Multi-Channel Convolutional Neural Networks Architecture Feeding for Effective EEG Mental Tasks Classification, Sensors 18(10), 3451 (2018)

4. Tarasiuk, P., Pryczek, M.: Geometric transformations embedded into convolutional neural networks. J. Appl. Comput. Sci. 24(3), 33–48 (2016)

5. Harár, P., Burget, R., Dutta, M.K.: Speech emotion recognition with deep learning. In: Proceedings of 4th International Conference on Signal Processing and Integrated Networks (SPIN), pp. 137–140 (2017)

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