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3 research outcomes, page 1 of 1
  • publication . Article . 2017
    Open Access
    Authors:
    Longyue Wang; Zhaopeng Tu; Xiaojun Zhang; Siyou Liu; Hang Li; Andy Way; Qun Liu;
    Persistent Identifiers
    Publisher: Springer Science and Business Media LLC
    Project: SFI | ADAPT: Centre for Digital... (13/RC/2106)

    A significant challenge for machine translation (MT) is the phenomena of dropped pronouns (DPs), where certain classes of pronouns are frequently dropped in the source language but should be retained in the target language. In response to this common problem, we propose...

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  • publication . Preprint . Article . 2018
    Open Access English
    Authors:
    Filip Klubička; Antonio Toral; Víctor M. Sánchez-Cartagena;
    Persistent Identifiers
    Project: SFI | ADAPT: Centre for Digital... (13/RC/2106), SNSF | Regional Linguistic Data ... (IZ74Z0_160501), EC | ABU-MATRAN (324414)

    This paper presents a quantitative fine-grained manual evaluation approach to comparing the performance of different machine translation (MT) systems. We build upon the well-established Multidimensional Quality Metrics (MQM) error taxonomy and implement a novel method t...

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  • publication . Article . 2011
    Open Access
    Authors:
    Sharon O'Brien;
    Persistent Identifiers
    Publisher: Springer Science and Business Media LLC
    Project: SFI | CSET CNGL: Next Generatio... (07/CE/I1142)

    Machine translation (MT) quality is generally measured via automatic metrics, producing scores that have no meaning for translators who are required to post-edit MT output or for project managers who have to plan and budget for transla- tion projects. This paper investi...

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3 research outcomes, page 1 of 1