The need for intrinsically safe access to driver information systems and other noncritical automotive functions is a pressing one and needs no elaboration. Voice access systems have been proposed for this. The authors describe the results of an initial investigation into the use of time encoded speech (TES) fixed size, fixed dimension A-matrices as the input layer of a simple neural network, configured to recognise the digits 'zero' to 'nine' from a male and from a female speaker. Input speech data recorded in an environment of 75 dB SPL background noise is first formed into 'A' matrices and then presented to the network. Subsequently, this same data is partially mutilated to mimic, to a first order, the effects of additional acoustic background noise. The network involved is a modification of the back error propagation algorithm based on the generalised delta rule.


    Access

    Access via TIB

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    The application of artificial neural networks to provide safe access to driver information systems and other noncritical automotive functions


    Additional title:

    Einsatz künstlicher neuronaler Netze für den sicheren Zugriff zu Fahrerinformationssystemen und anderen unkritischen Fahrzeugfunktionen


    Contributors:


    Publication date :

    1991


    Size :

    5 Seiten, 8 Quellen



    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English






    Thermal sensations and artificial neural networks: application to automotive car comfort

    Hermandez-Gress,N.M / Piniec,S. / Esteve,D. et al. | Automotive engineering | 1997


    Thermal sensations and artificial neural networks: application to automotive car comfort

    Hernandez-Gress, N. / Esteve, D. / Piniec, S. et al. | British Library Conference Proceedings | 1997


    Non-intrusive driver drowsiness monitoring via artificial neural networks

    Culp,J. / El-Gindy,M. / Haque,M.A. et al. | Automotive engineering | 2008