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A Task-Oriented Multi-turn Dialogue Mechanism for the Smart Cockpit

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Web and Big Data (APWeb-WAIM 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14332))

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Abstract

As an important carrier and platform for AI applications, the dialogue system for smart cockpits will become an important scenario for AI applications. However, there are some problems with the existing smart cockpit dialogue system, such as a lack of relevant corpus and knowledge annotations. These problems lead to the low accuracy of response representation generated by task-oriented dialogue systems for smart cockpits, which cannot meet the needs of smart human-computer interaction. To this end, this paper designs cockpitWOZ, a multi-round Chinese conversation dataset with knowledge annotation in the smart cockpit domain, which contains 2.9k conversations in four domains, including restaurants, attractions, music, and itineraries. On this basis, a new knowledge-driven task-based dialogue model is designed in this paper based on multiple baseline models. Firstly, a knowledge graph named cockpitKG based on the smart cockpit scenario is constructed to enhance the responsiveness of the model. Secondly, the smart cockpit system is built and a label replacement method is used to meet the requirements for real-time interaction during vehicle movement. Finally, the experimental results show that this model outperforms the baseline model and demonstrates that the introduction of background knowledge and label replacement can lead to higher-quality responses in the smart cockpit dialogue system.

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Authors and Affiliations

  1. College of Computer Science and Technology, Wuhan University of Science and Technology, Wuhan, 430065, China

    Xiaoyu Yang, Xinyi Sheng & Jinguang Gu

  2. Institute of Big Data Science and Engineering, Wuhan University of Science and Technology, Wuhan, 430065, China

    Jinguang Gu

  3. Key Laboratory of Rich-media Knowledge Organization and Service of Digital Publishing Content, National Press and Publication Administration, Beijing, 100038, China

    Jinguang Gu

Authors
  1. Xiaoyu Yang
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  2. Xinyi Sheng
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  3. Jinguang Gu
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Corresponding author

Correspondence to Jinguang Gu .

Editor information

Editors and Affiliations

  1. Peng Cheng Laboratory, Shenzhen, China

    Xiangyu Song

  2. China University of Geosciences, Wuhan, China

    Ruyi Feng

  3. China University of Geosciences, Wuhan, China

    Yunliang Chen

  4. Deakin University, Burwood, VIC, Australia

    Jianxin Li

  5. University of Exeter, Exeter, UK

    Geyong Min

A Appendix: Figure from “A Situation Knowledge Graph Construction Mechanism with Context-Aware Services for Smart Cockpit (submit to APWEB-WAIM2023)”

A Appendix: Figure from “A Situation Knowledge Graph Construction Mechanism with Context-Aware Services for Smart Cockpit (submit to APWEB-WAIM2023)”

Fig. 6.
figure 6

Smart cockpit ontology model.

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© 2024 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Yang, X., Sheng, X., Gu, J. (2024). A Task-Oriented Multi-turn Dialogue Mechanism for the Smart Cockpit. In: Song, X., Feng, R., Chen, Y., Li, J., Min, G. (eds) Web and Big Data. APWeb-WAIM 2023. Lecture Notes in Computer Science, vol 14332. Springer, Singapore. https://doi.org/10.1007/978-981-97-2390-4_22

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  • DOI: https://doi.org/10.1007/978-981-97-2390-4_22

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-97-2389-8

  • Online ISBN: 978-981-97-2390-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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