Speech Emotion Recognition Enhanced Traffic Efficiency Solution for Autonomous Vehicles in a 5G-Enabled Space-Air-Ground Integrated Intelligent Transportation System
文献类型：期刊论文
| 作者 | Tan, Liang6,7; Yu, Keping5; Lin, Long7; Cheng, Xiaofan7; Srivastava, Gautam3,4; Lin, Jerry Chun-Wei2; Wei, Wei1 |
| 刊名 | IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
 |
| 出版日期 | 2021-10-27 |
| 页码 | 13 |
| 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 |
| ISSN号 | 1524-9050 |
| DOI | 10.1109/TITS.2021.3119921 |
| 英文摘要 | 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. |
| 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 |
| 语种 | 英语 |
| WOS记录号 | WOS:000732070400001 |
| 出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
| 源URL | [http://119.78.100.204/handle/2XEOYT63/17970]  |
| 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.Xian Univ Technol, Sch Comp Sci & Engn, Xian 710048, Peoples R China 2.Western Norway Univ Appl Sci, Dept Comp Sci Elect Engn & Math Sci, N-5063 Bergen, Norway 3.China Med Univ, Res Ctr Interneural Comp, Taichung 40402, Taiwan 4.Brandon Univ, Dept Comp Sci, Brandon, MB R7A 6A9, Canada 5.Waseda Univ, Global Informat & Telecommun Inst, Tokyo 1698050, Japan 6.Chinese Acad Sci, Inst Comp Technol, Beijing 100190, Peoples R China 7.Sichuan Normal Univ, Coll Comp Sci, Chengdu 610101, 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. |
入库方式： OAI收割
来源：计算技术研究所
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