Research Article
Research on Quantitative Models and Correlation of QoE Testing for Vehiclar Voice Cloud Services
@INPROCEEDINGS{10.1007/978-3-030-72792-5_55, author={Yuxin Li and Kailiang Zhang and Lei Chen and Yuan An and Ping Cui}, title={Research on Quantitative Models and Correlation of QoE Testing for Vehiclar Voice Cloud Services}, proceedings={Simulation Tools and Techniques. 12th EAI International Conference, SIMUtools 2020, Guiyang, China, August 28-29, 2020, Proceedings, Part I}, proceedings_a={SIMUTOOLS}, year={2021}, month={4}, keywords={QoE FAHP MoS Vehicular unit}, doi={10.1007/978-3-030-72792-5_55} }- Yuxin Li
Kailiang Zhang
Lei Chen
Yuan An
Ping Cui
Year: 2021
Research on Quantitative Models and Correlation of QoE Testing for Vehiclar Voice Cloud Services
SIMUTOOLS
Springer
DOI: 10.1007/978-3-030-72792-5_55
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.
