Multi-classification speech emotion recognition based on two-stage bottleneck features selection and MCJD algorithm

Author:

Sun Linhui,Huang Yiqing,Li Qiu,Li Pingan

Funder

the National Natural Science Foundation of China

the Natural Science Foundation of the Jiangsu Higher Education Institutions of China

Publisher

Springer Science and Business Media LLC

Subject

Electrical and Electronic Engineering,Signal Processing

Reference28 articles.

1. Zhang, Z., Coutinho, E., Deng, J., et al.: Cooperative learning and its application to emotion recognition from speech. IEEE/ACM Trans. Audio Speech Lang. Proc. 23(1), 115–126 (2015)

2. Tahon, M., Devillers, L.: Towards a small set of robust acoustic features for emotion recognition: challenges. IEEE/ACM Trans. Audio Speech Lang. Proc. 24(1), 16–28 (2016)

3. Sun, L., Fu, S., Wang, F.: Decision tree SVM model with Fisher feature selection for speech emotion recognition. J Audio Speech Music Proc. 2019, 2 (2019)

4. Chuang, Z.J., Wu, C.H.: Emotion recognition using acoustic features and textual content. In: 2004 IEEE International Conference on Multimedia and Expo (ICME) (IEEE Cat. No.04TH8763), Taipei, vol. 1, pp. 53–56 (2004).

5. Sun, L., Zou, B., Fu, S., et al.: Speech emotion recognition based on DNN-decision tree SVM model. Speech Commun. 115, 29–37 (2019)

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