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Tesla Voice Assistant Network Public Opinion Analysis

In: Proceedings of the 2025 7th International Conference on Economic Management and Cultural Industry (ICEMCI 2025)

Author

Listed:
  • Yuhan Gao

    (China University of Mining & Technology, School of Science)

  • Yibo Liu

    (The Hong Kong Polytechnic University, Institute of Computer and Mathematical Science)

  • Xinyi Miao

    (Henan University of Economics and Law, School of Business Administration)

Abstract

As a benchmark in the field of new energy vehicles and intelligent technology, Tesla’s voice assistant encountered significant bottlenecks when entering the domestic market. At present, although most users acknowledge that the voice assistant can provide stable responses to basic commands, they also point out many obvious shortcomings, such as insufficient scalability of functions, easy system crashes during operation, and limited execution of some complex instructions due to hardware performance constraints. In response to these issues, this article specifically proposes a phased improvement plan. Short term focus on unleashing the potential of core functions to ensure smooth basic experience; Mid term efforts will be made to enhance spatial adaptability and meet the diverse needs of various scenarios; Long term planning for overall architecture upgrade, laying the foundation for future development. At the same time, focus on balancing technological innovation and user experience throughout the process, optimizing communication logic and data processing, comprehensively enhancing entertainment interaction experience, and building differentiated competitive advantages.

Suggested Citation

  • Yuhan Gao & Yibo Liu & Xinyi Miao, 2025. "Tesla Voice Assistant Network Public Opinion Analysis," Advances in Economics, Business and Management Research, in: Abdelhak Senadjki & Chee Yoong Liew & Yahua Xu & Fong Peng Chew (ed.), Proceedings of the 2025 7th International Conference on Economic Management and Cultural Industry (ICEMCI 2025), pages 721-731, Springer.
    • Handle: RePEc:spr:advbcp:978-94-6463-888-2_69
    DOI: 10.2991/978-94-6463-888-2_69
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