Air traffic controllers normally manage all aircraft information with flight strips. These strips contain static information about each flight such as call sign or weight category. Additionally, all clearances regarding altitude, speed, and direction are noted by the controller. Historically paper flight strips were in operation, but modern controller working positions use electronic flight strips or electronic aircraft labels. However, independent from the type, considerable controller effort is needed to manually maintain strip information consistent with commands given to the aircraft. Automatic Speech Recognition (ASR) is a solution which requires no additional work from the controller to maintain radar label information. The Assistant Based Speech Recognizer developed by DLR and Saarland University enables command error rates below 2%. Validation trials with controllers from Germany and Austria showed that workload reduction by a factor of three for label maintenance is possible.


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    Titel :

    Reducing controller workload with automatic speech recognition


    Beteiligte:


    Erscheinungsdatum :

    2016-09-01


    Format / Umfang :

    640515 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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