Speech Emotion Recognition Enhanced Traffic Efficiency Solution for Autonomous Vehicles in a 5G-Enabled Space-Air-Ground Integrated Intelligent Transportation System

doi:10.1109/TITS.2021.3119921

	Speech Emotion Recognition Enhanced Traffic Efficiency Solution for Autonomous Vehicles in a 5G-Enabled Space-Air-Ground Integrated Intelligent Transportation System
	Tan, Liang 1,2; Yu, Keping 3; Lin, Long 1; Cheng, Xiaofan 1; Srivastava, Gautam 4,5; Lin, Jerry Chun-Wei 6; Wei, Wei 7
	2021-10-27
发表期刊	IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
ISSN	1524-9050
页码	13
摘要	Speech emotion recognition (SER) is becoming the main human-computer interaction logic for autonomous vehicles in the next generation of intelligent transportation systems (ITSs). It can improve not only the safety of autonomous vehicles but also the personalized in-vehicle experience. However, current vehicle-mounted SER systems still suffer from two major shortcomings. One is the insufficient service capacity of the vehicle communication network, which is unable to meet the SER needs of autonomous vehicles in next-generation ITSs in terms of the data transmission rate, power consumption, and latency. Second, the accuracy of SER is poor, and it cannot provide sufficient interactivity and personalization between users and vehicles. To address these issues, we propose an SER-enhanced traffic efficiency solution for autonomous vehicles in a 5G-enabled space-air-ground integrated network (SAGIN)-based ITS. First, we convert the vehicle speech information data into spectrograms and input them into an AlexNet network model to obtain the high-level features of the vehicle speech acoustic model. At the same time, we convert the vehicle speech information data into text information and input it into the Bidirectional Encoder Representations from Transformers (BERT) model to obtain the high-level features of the corresponding text model. Finally, these two sets of high-level features are cascaded together to obtain fused features, which are sent to a softmax classifier for emotion matching and classification. Experiments show that the proposed solution can improve not only the SAGIN's service capabilities, resulting in a large capacity, high bandwidth, ultralow latency, and high reliability, but also the accuracy of vehicle SER as well as the performance, practicality, and user experience of the ITS.
关键词	Speech recognition Autonomous vehicles Satellites Emotion recognition Next generation networking Computer science Communication networks Speech emotion recognition autonomous vehicles artificial intelligence 5G-enabled SAGIN ITS
DOI	10.1109/TITS.2021.3119921
收录类别	SCI
语种	英语
资助项目	National Natural Science Foundation of China[61373162] ; Sichuan Provincial Science and Technology Department Project[2019YFG0183] ; Sichuan Provincial Key Laboratory Project[KJ201402] ; Japan Society for the Promotion of Science (JSPS)[JP18K18044] ; Japan Society for the Promotion of Science (JSPS)[JP21K17736]
WOS研究方向	Engineering ; Transportation
WOS类目	Engineering, Civil ; Engineering, Electrical & Electronic ; Transportation Science & Technology
WOS记录号	WOS:000732070400001
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
引用统计	被引频次：116[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/17971
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Yu, Keping
作者单位	1.Sichuan Normal Univ, Coll Comp Sci, Chengdu 610101, Peoples R China 2.Chinese Acad Sci, Inst Comp Technol, Beijing 100190, Peoples R China 3.Waseda Univ, Global Informat & Telecommun Inst, Tokyo 1698050, Japan 4.Brandon Univ, Dept Comp Sci, Brandon, MB R7A 6A9, Canada 5.China Med Univ, Res Ctr Interneural Comp, Taichung 40402, Taiwan 6.Western Norway Univ Appl Sci, Dept Comp Sci Elect Engn & Math Sci, N-5063 Bergen, Norway 7.Xian Univ Technol, Sch Comp Sci & Engn, Xian 710048, Peoples R China
推荐引用方式 GB/T 7714	Tan, Liang,Yu, Keping,Lin, Long,et al. Speech Emotion Recognition Enhanced Traffic Efficiency Solution for Autonomous Vehicles in a 5G-Enabled Space-Air-Ground Integrated Intelligent Transportation System[J]. IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS,2021:13.
APA	Tan, Liang.,Yu, Keping.,Lin, Long.,Cheng, Xiaofan.,Srivastava, Gautam.,...&Wei, Wei.(2021).Speech Emotion Recognition Enhanced Traffic Efficiency Solution for Autonomous Vehicles in a 5G-Enabled Space-Air-Ground Integrated Intelligent Transportation System.IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS,13.
MLA	Tan, Liang,et al."Speech Emotion Recognition Enhanced Traffic Efficiency Solution for Autonomous Vehicles in a 5G-Enabled Space-Air-Ground Integrated Intelligent Transportation System".IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS (2021):13.