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

    Cite this

    Martinez, M. G., Singla, K., Tammewar, A., Mesa-Lao, B., Thakur, A., Anusuya, M. A., ... Carl, M. (2014). SEECAT: ASR & Eye-tracking Enabled Computer Assisted Translation. In M. Tadić, P. Koehn, J. Roturier, & A. Way (Eds.), Proceedings of the 17th Annual Conference of the European Association for Machine Translation: EAMT2014 (pp. 81-88). Basel: European Association for Machine Translation.
    Martinez, Mercedes Garcia ; Singla, Karan ; Tammewar, Aniruddha ; Mesa-Lao, Bartolomé ; Thakur, Ankita ; Anusuya, M. A. ; Srinivas, Banglore ; Carl, Michael. / SEECAT : ASR & Eye-tracking Enabled Computer Assisted Translation. Proceedings of the 17th Annual Conference of the European Association for Machine Translation: EAMT2014. editor / Marko Tadić ; Philipp Koehn ; Johann Roturier ; Andy Way. Basel : European Association for Machine Translation, 2014. pp. 81-88
    @inproceedings{a651a43c78334755829aa2a38b6c57f1,
    title = "SEECAT: ASR & Eye-tracking Enabled Computer Assisted Translation",
    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.",
    author = "Martinez, {Mercedes Garcia} and Karan Singla and Aniruddha Tammewar and Bartolom{\'e} Mesa-Lao and Ankita Thakur and Anusuya, {M. A.} and Banglore Srinivas and Michael Carl",
    year = "2014",
    language = "English",
    isbn = "9789535537533",
    pages = "81--88",
    editor = "Marko Tadić and Philipp Koehn and Johann Roturier and Andy Way",
    booktitle = "Proceedings of the 17th Annual Conference of the European Association for Machine Translation",
    publisher = "European Association for Machine Translation",
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    Martinez, MG, Singla, K, Tammewar, A, Mesa-Lao, B, Thakur, A, Anusuya, MA, Srinivas, B & Carl, M 2014, SEECAT: ASR & Eye-tracking Enabled Computer Assisted Translation. in M Tadić, P Koehn, J Roturier & A Way (eds), Proceedings of the 17th Annual Conference of the European Association for Machine Translation: EAMT2014. European Association for Machine Translation, Basel, pp. 81-88, Dubrovnik, Croatia, 16/06/2014.

    SEECAT : ASR & Eye-tracking Enabled Computer Assisted Translation. / Martinez, Mercedes Garcia; Singla, Karan; Tammewar, Aniruddha; Mesa-Lao, Bartolomé ; Thakur, Ankita; Anusuya, M. A.; Srinivas, Banglore; Carl, Michael.

    Proceedings of the 17th Annual Conference of the European Association for Machine Translation: EAMT2014. ed. / Marko Tadić; Philipp Koehn; Johann Roturier; Andy Way. Basel : European Association for Machine Translation, 2014. p. 81-88.

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

    TY - GEN

    T1 - SEECAT

    T2 - ASR & Eye-tracking Enabled Computer Assisted Translation

    AU - Martinez, Mercedes Garcia

    AU - Singla, Karan

    AU - Tammewar, Aniruddha

    AU - Mesa-Lao, Bartolomé

    AU - Thakur, Ankita

    AU - Anusuya, M. A.

    AU - Srinivas, Banglore

    AU - Carl, Michael

    PY - 2014

    Y1 - 2014

    N2 - 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.

    AB - 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.

    M3 - Article in proceedings

    SN - 9789535537533

    SP - 81

    EP - 88

    BT - Proceedings of the 17th Annual Conference of the European Association for Machine Translation

    A2 - Tadić, Marko

    A2 - Koehn, Philipp

    A2 - Roturier, Johann

    A2 - Way, Andy

    PB - European Association for Machine Translation

    CY - Basel

    ER -

    Martinez MG, Singla K, Tammewar A, Mesa-Lao B, Thakur A, Anusuya MA et al. SEECAT: ASR & Eye-tracking Enabled Computer Assisted Translation. In Tadić M, Koehn P, Roturier J, Way A, editors, Proceedings of the 17th Annual Conference of the European Association for Machine Translation: EAMT2014. Basel: European Association for Machine Translation. 2014. p. 81-88