In this paper we compare speaker clustering and speech recognition techniques to the problem of understanding patterns of air traffic control communications. For a given radio transmission, our goal is to identify the talker and to whom he/she is speaking. This information, in combination with knowledge of the the roles (i.e. takeoff, approach, hand-off, taxi, etc.) of different radio frequencies within an air traffic control region could allow tracking of pilots through various stages of flight, thus providing the potential to monitor the airspace in great detail. Both techniques must contend with degraded audio channels and significant non-native accents.


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    Titel :

    Comparison of Speaker Clustering and Speech Recognition Techniques for Air Situational Awareness


    Beteiligte:
    W. Shen (Autor:in) / D. Reynolds (Autor:in)

    Erscheinungsdatum :

    2015


    Format / Umfang :

    4 pages


    Medientyp :

    Report


    Format :

    Keine Angabe


    Sprache :

    Englisch




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