Theoretical and Natural Science

Theoretical and Natural Science

TNS Vol.2 (CIAP 2022), 02 February 2023

Open Access | Article

Research on Intelligent Dialogue Systems

Siyi Hu 1
1 Arizona State University, Tempe, Arizona, 85281, United States

* Author to whom correspondence should be addressed.

Theoretical and Natural Science, TNS Vol.2 (CIAP 2022), 203-210
Published 02 February 2023. © 2023 The Author(s). Published by EWA Publishing
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Citation Siyi Hu. Research on Intelligent Dialogue Systems. TNS (2023) TNS Vol.2 (CIAP 2022): 203-210.


Intelligent dialogue systems, as a subfield of artificial intelligence, have very important research significance and application value. Today’s AI dialogue systems are still in a relatively early stage, but they are developing very rapidly. In recent years, intelligent dialogue systems have been applied in many fields, such as intelligent customer service in online transactions, intelligent voice assistants in smartphones, and virtual chatbots. This paper introduces the background of intelligent dialogue systems and the current research status of key technologies and discusses some challenges in this field and some recent research to improve the system. Most of the current intelligent dialogue systems can perform effective human-computer interaction and respond accordingly. But for the next generation of intelligent dialogue system, more human characteristics are needed so that it can better understand and express human language, have its own personality, and maintain the consistency and logic of dialogue.


Natural language processing, Artificial intelligence, Intelligent dialogue system, Chatbot


1. Nicola Bleu. (2021) 29 Top Chatbot Statistics For 2022: Usage, Demographics, Trends. Blogging Wizard. Retrieved June 30, 2022 from

2. Ciarán Daly. (2018) KLM: Chatbots Are The Future Of Customer Support. AI Business. Retrieved June 30, 2022 from

3. Turing, A. M. (2012) Computing machinery and intelligence (1950). The Essential Turing: the Ideas That Gave Birth to the Computer Age, 433-464.

4. WEIZENBAUM J. (1983) ELIZA-a computer program for the study of natural language communication between man and machine[J]. Communications of the ACM,26(1): 23-28.

5. Bayan AbuShawar and Eric Atwell. (2015) ALICE Chatbot: Trials and Outputs. Computación y Sistemas 19, 4. DOI:

6. Cahn, J. (2017) CHATBOT: Architecture, design, & development. University of Pennsylvania School of Engineering and Applied Science Department of Computer and Information Science.

7. Shum, H. Y., He, X. D., & Li, D. (2018) From Eliza to XiaoIce: challenges and opportunities with social chatbots. Frontiers of Information Technology & Electronic Engineering, 19(1), 10-26.

8. Karpagavalli, S., & Chandra, E. (2016) A review on automatic speech recognition architecture and approaches. International Journal of Signal Processing, Image Processing and Pattern Recognition, 9(4), 393-404.

9. Prakash M Nadkarni, Lucila Ohno-Machado, Wendy W Chapman. (2011) Natural language processing: an introduction, Journal of the American Medical Informatics Association, Volume 18, Issue 5, Pages 544–551

10. Cambria, E., & White, B. (2014) Jumping NLP curves: A review of natural language processing research. IEEE Computational intelligence magazine, 9(2), 48-57.

11. Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A. N., ... & Polosukhin, I. (2017) Attention is all you need. Advances in neural information processing systems, 30.

12. Poria, S., Majumder, N., Mihalcea, R., & Hovy, E. (2019) Emotion recognition in conversation: Research challenges, datasets, and recent advances. IEEE Access, 7, 100943-100953.

13. Jia Xibin, Li Rang, Hu Changjian, Chen Juncheng. (2017) A Review of Research on Intelligent Dialogue Systems.

14. Gao, J., Galley, M., & Li, L. (2019) Neural approaches to conversational AI: Question answering, task-oriented dialogues and social chatbots. Now Foundations and Trends.

15. Serban, I., Sordoni, A., Bengio, Y., Courville, A., & Pineau, J. (2016) Building end-to-end dialogue systems using generative hierarchical neural network models. In Proceedings of the AAAI Conference on Artificial Intelligence (Vol. 30, No. 1).

16. Sutskever, I., Vinyals, O., & Le, Q. V. (2014) Sequence to sequence learning with neural networks. Advances in neural information processing systems, 27.

17. Eli Collins. (2021) LaMDA: our breakthrough conversation technology. Google. Retrieved July 3, 2022 from

18. Li Zhou, Jianfeng Gao, Di Li, Heung-Yeung Shum. (2020) The Design and Implementation of XiaoIce, an Empathetic Social Chatbot. Computational Linguistics 46 (1): 53–93.

19. Jiqizhixin (2021) How long is there to go for the next generation of intelligent dialogue systems that speak as naturally and fluently as people?. Retrieved July 3, 2022 from

20. Jaehun Jung, Bokyung Son, and Sungwon Lyu. (2020) AttnIO: Knowledge Graph Exploration with In-and-Out Attention Flow for Knowledge-Grounded Dialogue. In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing(EMNLP), pp. 3484–3497, Online. Association for Computational Linguistics.

21. Zheng, Y., Zhang, R., Huang, M., & Mao, X. (2020, April) A pre-training based personalized dialogue generation model with persona-sparse data. In Proceedings of the AAAI Conference on Artificial Intelligence.Vol. 34, No. 05, pp. 9693-9700.

Data Availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

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