Improving Language Learning Performance Using Multimodal Dialogue Systems

Zhenyu Wu; Zhiyang Ding; Zhaowei Zhang; Yanqin Mao

doi:10.2991/978-94-6463-242-2_23

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Improving Language Learning Performance Using Multimodal Dialogue Systems

Authors

Zhenyu Wu¹^{, *}, Zhiyang Ding¹, Zhaowei Zhang¹, Yanqin Mao²

¹School of Internet of Things, Nanjing University of Posts and Telecommunications, Nanjing, China

²School of Software, Nanjing University of Posts and Telecommunications, Nanjing, China

^*Corresponding author. Email: zhenyu.wu@njupt.edu.cn

Corresponding Author

Zhenyu Wu

Available Online 22 September 2023.

DOI: 10.2991/978-94-6463-242-2_23 How to use a DOI?
Keywords: language learning; natural language processing; multimodal interaction; multimodal dialogue system
Abstract: Learning a language poses a significant challenge for learners, who must comprehend the intricacies of language and analyze the relationships among its components. While computer technologies have been developed to assist language learning, they fail to mirror the human cognitive process. This paper examines the application of a multimodal dialogue system to enhance language learning outcomes. The system boasts several advantages. Firstly, smart devices can collect multimodal data in learning environments to monitor the learner’s status in real-time, thus enhancing the accuracy of intention recognition. Secondly, the system can interact with learners naturally by analyzing their multimodal data, resulting in improved language skills. Finally, application scenarios are designed based on the defined multimodal dialogue system, which effectively demonstrates the system’s ability to enhance language learning performance.
Copyright: © 2024 The Author(s)
Open Access: Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title: Proceedings of the 2023 4th International Conference on Artificial Intelligence and Education (ICAIE 2023)
Series: Atlantis Highlights in Computer Sciences
Publication Date: 22 September 2023
ISBN: 10.2991/978-94-6463-242-2_23
ISSN: 2589-4900
DOI: 10.2991/978-94-6463-242-2_23 How to use a DOI?
Open Access: Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

ris enw bib

TY  - CONF
AU  - Zhenyu Wu
AU  - Zhiyang Ding
AU  - Zhaowei Zhang
AU  - Yanqin Mao
PY  - 2023
DA  - 2023/09/22
TI  - Improving Language Learning Performance Using Multimodal Dialogue Systems
BT  - Proceedings of the 2023 4th International Conference on Artificial Intelligence and Education (ICAIE 2023)
PB  - Atlantis Press
SP  - 191
EP  - 197
SN  - 2589-4900
UR  - https://doi.org/10.2991/978-94-6463-242-2_23
DO  - 10.2991/978-94-6463-242-2_23
ID  - Wu2023
ER  -

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