SEECAT: ASR & Eye-tracking Enabled Computer Assisted Translation

Mercedes Garcia Martinez, Karan Singla, Aniruddha Tammewar, Bartolomé Mesa-Lao, Ankita Thakur, M. A. Anusuya, Banglore Srinivas, Michael Carl

    Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

    Abstract

    Typing has traditionally been the only input method used by human translators working with computer-assisted translation (CAT) tools. However, speech is a natural communication channel for humans and, in principle, it should be faster and easier than typing from a keyboard. This contribution investigates the integration of automatic speech recognition (ASR) in a CAT workbench testing its real use by human translators while post-editing machine translation (MT) outputs. This paper also explores the use of MT combined with ASR in order to improve recognition accuracy in a workbench integrating eye-tracking functionalities to collect process-oriented information about translators’ performance.
    Original languageEnglish
    Title of host publicationProceedings of the 17th Annual Conference of the European Association for Machine Translation : EAMT2014
    EditorsMarko Tadić, Philipp Koehn, Johann Roturier, Andy Way
    Place of PublicationBasel
    PublisherEuropean Association for Machine Translation
    Publication date2014
    Pages81-88
    ISBN (Print)9789535537533
    Publication statusPublished - 2014
    EventThe 17th Annual Conference of the European Association for Machine Translation. EAMT 2014 - The Centre for Advanced Academic Studies , Dubrovnik, Croatia
    Duration: 16 Jun 201418 Jun 2014
    Conference number: 17
    http://hnk.ffzg.hr/eamt2014/

    Conference

    ConferenceThe 17th Annual Conference of the European Association for Machine Translation. EAMT 2014
    Number17
    LocationThe Centre for Advanced Academic Studies
    CountryCroatia
    CityDubrovnik
    Period16/06/201418/06/2014
    Internet address

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