This paper describes a method to validate in-vehicle speech recognition by combining synthetically mixed speech and noise samples with batch speech recognition. Vehicle cabin noises are prerecorded along with the impulse response from the driver's mouth location to the cabin microphone location. These signals are combined with a catalog of speech utterances to generate a noisy speech corpus. Several factors were examined to measure their relative importance on speech recognition robustness. These include road surface and vehicle speed, climate control blower noise, and driver's seat position. A summary of the main effects from these experiments are provided with the most significant factors coming from climate control noise. Additionally, a Signal to Noise Ratio (SNR) experiment was conducted highlighting the inverse relationship with speech recognition performance.


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    Title :

    Validation of In-Vehicle Speech Recognition Using Synthetic Mixing


    Additional title:

    Sae International Journal of Passenger Cars- Electronic and Electrical Systems
    Sae Int. J. Passeng. Cars – Electron. Electr. Syst


    Contributors:

    Conference:

    WCX™ 17: SAE World Congress Experience ; 2017



    Publication date :

    2017-03-28


    Size :

    5 pages




    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English




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