1. Deep learning library (2020). https://pytorch.org/. Accessed 4 Oct 2020
2. He, K., Zhang, X., Ren, S., Sun, J.: Deep residual learning for image recognition. CoRR abs/1512.03385 (2015). http://arxiv.org/abs/1512.03385
3. Hochreiter, S., Bengio, Y., Frasconi, P., Schmidhuber, J.: Gradient flow in recurrent nets: the difficulty of learning long-term dependencies. In: Kremer, S.C., Kolen, J.F. (eds.) A Field Guide to Dynamical Recurrent Neural Networks. IEEE Press (2001)
4. Ishi, C., Ishiguro, H., Hagita, N.: Using prosodic and voice quality features for paralinguistic information extraction. In: Proceedings of the Speech Prosody 2006, pp. 883–886, Dresden (2006)
5. Karpov, A.A., Kaya, H., Salakh, A.A.: Actual problems and achievements of paralinguistic speech analysis. Nauchno-tekhnicheskiy vestnik informatsionnykh tekhnologiy, mekhaniki i optiki 16(4), 581–592 (2016). (in Russian)