Intelligent Customer Service System Based on Speech Emotion Recognition-Reference-Cited by-同舟云学术

Intelligent Customer Service System Based on Speech Emotion Recognition

Published:2023-10-20 Issue: Volume: Page:334-338
ISSN:
Container-title:Proceedings of the 2023 7th International Conference on Electronic Information Technology and Computer Engineering
language:
Short-container-title:

Author:

Zheng Zhiguo¹^ORCID,Chen Jie²^ORCID,Li Shuaijie²^ORCID,Sun Jiapeng²^ORCID,Xie Yihan²^ORCID,Liang Lijuan³^ORCID

Affiliation:

1. School of Information Engineering, Hainan Vocational University of Science and Technology,Haikou,china, China and School of Information and Communication Engineering,, Hainan University,, China

2. School of Information Engineering, Hainan Vocational University of Science and Technology,Haikou,china, China

3. The First Affiliated Hospital of Hainan Medical University,Haikou,china, China

Funder

Supported by Science and Technology special fund of Hainan Province

Was supported by the Hainan Province Natural Science Foundation of China

Supported by the Hainan Province Natural Science Foundation of China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3650400.3650454

Reference11 articles.

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2. Stappen, L., Baird, A., Christ, L., Schumann, L., Sertolli, B., Messner, E. M., ... & Schuller, B. W. 2021. The MuSe 2021 multimodal sentiment analysis challenge: sentiment, emotion, physiological-emotion, and stress. In Proceedings of the 2nd on Multimodal Sentiment Analysis Challenge (pp. 5-14)

3. Koolagudi S. G. & Rao K. S. 2012. Emotion recognition from speech: a review. International journal of speech technology 15 99-117.

4. Dileep A. D. & Sekhar C. C. 2013. GMM-based intermediate matching kernel for classification of varying lengt patterns of long duration speech using support vector machines. IEEE Transactions on Neural Networks and Learning Systems 25(8) 1421-1432.

5. Deng L. & Yu D. 2014. Deep learning: methods and applications. Foundations and trends® in signal processing 7(3–4) 197-387.