With driving emerging as a common mode of transportation, the automotive industry has increasingly prioritized driving safety and experience. A substantial body of research focused on driving safety and the overall travel experience has underscored the pivotal role of emotions. In this article, we introduce an innovative in-car emotion recognition and interaction system, carefully crafted to intelligently respond to the emotional states of drivers. This system captures real-time emotional data through its user input layer and seamlessly integrates it into the technological architecture layer, residing within the vehicle's CPU. Leveraging cutting-edge deep learning models for emotion recognition, the system's outcomes trigger tailored emotion regulation strategies within the interaction feedback layer. Notably, our study introduces a groundbreaking speech fusion feature, MFCCs+, meticulously crafted for driving contexts. Furthermore, we have optimized the driving speech emotion recognition model using 1D-CNN, resulting in a remarkable 10% improvement in recognition accuracy. Subsequent validation experiments affirm the system's effectiveness in enhancing driving safety. In conclusion, the integration of emotion-based interaction solutions holds immense potential for elevating both driving safety and the overall travel experience within intelligent driving scenarios. This innovation promises to shape the future landscape of automotive travel, offering a safer and more enjoyable journey for all.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Intelligent In-Car Emotion Regulation Interaction System Based on Speech Emotion Recognition


    Contributors:
    Yang, Yuhan (author) / Zhang, Yan (author) / Zhong, Zhinan (author) / Dai, Wan (author) / Chen, Yunfei (author) / Chen, Mo (author)


    Publication date :

    2024-04-19


    Size :

    2178164 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Speech-Based Driver Emotion Recognition

    Tan, Haiqiu / Zhang, Haodong / Shi, Jian et al. | TIBKAT | 2023


    Speech-Based Driver Emotion Recognition

    Tan, Haiqiu / Zhang, Haodong / Shi, Jian et al. | Springer Verlag | 2022


    Speech Emotion Recognition of Intelligent Virtual Companion for Solitudinarian

    Alnahhas, Mutaz / Haw, Tan Wooi / Pun, Ooi Chee | Springer Verlag | 2022

    Free access

    Emotion recognition for artificially-intelligent system

    European Patent Office | 2021

    Free access

    Emotion recognition for artificially-intelligent system

    SANGHO KIM / HONDSON KUANG | European Patent Office | 2022

    Free access