Enhancing Intelligent Voice Assistants in Tourism Services A Computational Approach

DOI

10.2991/978-2-38476-346-7_6How to use a DOI?

Keywords

intelligent voice assistant; travel service; speech recognition; natural language processing

Abstract

This study aims to enhance the response efficiency of intelligent voice assistants in tourism industry services by analyzing technical performance improvements and application strategies. It thoroughly examines the application of these assistants in tourism, assessing their functionality in information retrieval, travel booking, payment services, navigation explanations, cross-language translation, customer opinion collection, and satisfaction evaluation. The paper then showcases how upgrading speech recognition and natural language processing technologies can optimize processing strategies and personalize services. Employing advanced computational models, such as Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs), the study enhances the assistants’ accuracy in noisy environments and multilingual natural language understanding. Additionally, large-scale multilingual pre-trained models like mBERT and mT5 are used to boost cross-cultural adaptability and language translation capabilities. By integrating these technologies, the research demonstrates significant enhancements in operational efficiency and user experience, thereby providing the tourism industry with more efficient and personalized service solutions through improved adaptability in complex linguistic and cultural environments.

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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TY  - CONF
AU  - Zhiyu Zhang
PY  - 2024
DA  - 2024/12/27
TI  - Enhancing Intelligent Voice Assistants in Tourism Services A Computational Approach
BT  - Proceeding of the 2024 International Conference on Diversified Education and Social Development (DESD 2024)
PB  - Atlantis Press
SP  - 33
EP  - 39
SN  - 2352-5398
UR  - https://doi.org/10.2991/978-2-38476-346-7_6
DO  - 10.2991/978-2-38476-346-7_6
ID  - Zhang2024
ER  -