Automated analysis of human affective behavior has attracted increasing attention in recent years. Driver's emotion often influences driving performance which can be improved if the car actively responds to the emotional state of the driver. It is important for an intelligent driver support system to accurately monitor the driver's state in an unobtrusive and robust manner. Ever changing environment while driving poses a serious challenge to existing techniques for speech emotion recognition. In this paper, we utilize contextual information of the outside environment as well as inside car user to improve the emotion recognition accuracy. In particular, a noise cancellation technique is used to suppress the noise adaptively based on the driving context and a gender based context information is analyzed for developing the classifier. Experimental analyses show promising results.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Speech based emotion classification framework for driver assistance system


    Contributors:


    Publication date :

    2010-06-01


    Size :

    1728999 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Speech Based Emotion Classification Framework for Driver Assistance System, pp. 174-178

    Tawari, A. / Trivedi, M.M. / Institute of Electrical and Electronics Engineers | British Library Conference Proceedings | 2010


    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


    Driver-assistance device, driver-assistance system, and driver-assistance program

    NAWA KAZUNARI / HAGIYA TOSHIYUKI | European Patent Office | 2022

    Free access

    DRIVER ASSISTANCE DEVICE, DRIVER ASSISTANCE METHOD, AND DRIVER ASSISTANCE SYSTEM

    HATO JUMPEI / ARII SHIORI / MATSUOKA BUNKEI et al. | European Patent Office | 2022

    Free access