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    Automatic Understanding of ATC Speech: Study of Prospectives and Field Experiments for Several Controller Positions

    TitleAutomatic Understanding of ATC Speech: Study of Prospectives and Field Experiments for Several Controller Positions
    Publication TypeJournal Article
    Año de publicación2011
    AutoresPardo, JM, Ferreiros, J, Fernandez, F, Sama, V, Cordoba, R, Macias-Guarasa, J, Montero, JM, San-Segundo, R, D'Haro, LF, Gonzalez, G
    Idioma de publicaciónEnglish
    JournalIEEE Transactions on Aerospace and Electronic Systems
    Volumen47
    Número4
    Páginas2709 – 2730
    Fecha de publicación10/2011
    EditorialIEEE
    Rank in category3/27
    JCR CategoryENGINEERING, AEROSPACE
    Palabras claveAir Traffic Control, Machine learning., Speech recognition, Speech Understanding
    JCR Impact Factor1.230
    ISSN0018-9251
    URLhttp://ieee-aess.org/sites/default/files/documents/t-aes/october2011/4742709.htm
    DOI10.1109/TAES.2011.6034660
    Abstract

    Although there has been a lot of interest in
    recognizing and understanding Air Traffic Control (ATC)
    speech, none of the published works have obtained detailed
    field data results. We have developed a system able to identify
    the language spoken and recognize and understand sentences
    in both Spanish and English. We also present field results for
    several in-tower controller positions. To the best of our
    knowledge, this is the first time that field ATC speech (not
    simulated) is captured, processed and analyzed. The use of
    stochastic grammars allows variations in the standard
    phraseology that appear in field data. The robust
    understanding algorithm developed has 95% concept accuracy
    from ATC text input. It also allows changes in the presentation
    order of the concepts and the correction of errors created by
    the speech recognition engine improving it by 17% and 25%
    respectively, absolute in the percentage of fully correctly
    understood sentences for English and Spanish in relation to the
    percentages of fully correctly recognized sentences. The
    analysis of errors due to the spontaneity of the speech and its
    comparison to read speech is also carried out. A 96% word
    accuracy for read speech is reduced to 86% word accuracy for
    field ATC data for Spanish for the “clearances” task
    confirming that field data is needed to estimate the
    performance of a system. A literature review and a critical
    discussion on the possibilities of speech recognition and
    understanding technology applied to ATC speech are also
    given.

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