Abstract
Vehicle voice cloud service can help drivers reduce the dependence on vehicle operation and improve driving safety. In the related test of automobile voice cloud service quality evaluation, the research of quantitative model is an important part. The research and analysis of quantitative index correlation can effectively optimize and improve the test system, provide strong objective evaluation support for operators and service providers, and enhance the core competitiveness. Voice cloud service is composed of many modules and involves many fields. The user’s business experience is closely related to the end-to-end transmission elements such as business category, terminal capability and occurrence scene. The traditional QoE (quality of experience) evaluation can not meet the evaluation requirements. Therefore, this paper uses the hierarchical method to build the key index system of automobile voice cloud service, puts forward the quantitative model of QoE test, and gives the key points The results show that the model has a high accuracy and can provide strong support for the evaluation and testing of related services for automobile voice cloud operators and service providers.
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Acknowledgements
This work is partly supported by Jiangsu technology project of Housing and Urban-Rural Development (No. 2018ZD265, No. 2019ZD039, No. 2019ZD040, No. 2019ZD041).
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Li, Y., Zhang, K., Chen, L., An, Y., Cui, P. (2021). Research on Quantitative Models and Correlation of QoE Testing for Vehiclar Voice Cloud Services. In: Song, H., Jiang, D. (eds) Simulation Tools and Techniques. SIMUtools 2020. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 369. Springer, Cham. https://doi.org/10.1007/978-3-030-72792-5_55
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