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19 research outcomes, page 1 of 2
  • publication . Preprint . 2020
    Open Access English
    Authors:
    Kocmi, Tom; Limisiewicz, Tomasz; Stanovsky, Gabriel;
    Project: EC | Bergamot (825303)

    Gender bias in machine translation can manifest when choosing gender inflections based on spurious gender correlations. For example, always translating doctors as men and nurses as women. This can be particularly harmful as models become more popular and deployed within...

  • publication . Conference object . Contribution for newspaper or weekly magazine . Preprint . 2020
    Open Access
    Authors:
    Rehm, Georg; Marheinecke, Katrin; Hegele, Stefanie; Piperidis, Stelios; Bontcheva, Kalina; Hajic, Jan; Choukri, Khalid; Vasiljevs, Andrejs; Backfried, Gerhard; Prinz, Christoph; ...
    Project: EC | ELG (825627), EC | AI4EU (825619), EC | BDVe (732630), SFI | ADAPT: Centre for Digital... (13/RC/2106), EC | X5gon (761758)

    Multilingualism is a cultural cornerstone of Europe and firmly anchored in the European treaties including full language equality. However, language barriers impacting business, cross-lingual and cross-cultural communication are still omnipresent. Language Technologies ...

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  • publication . Conference object . Preprint . 2020
    Open Access English
    Authors:
    Abdi Khojasteh, Hadi; Ansari, Ebrahim; Bohlouli, Mahdi;
    Publisher: HAL CCSD

    Language recognition has been significantly advanced in recent years by means of modern machine learning methods such as deep learning and benchmarks with rich annotations. However, research is still limited in low-resource formal languages. This consists of a significa...

  • publication . Article . Preprint . Conference object . 2020
    Open Access English
    Authors:
    Ulčar, Matej; Robnik-Šikonja, Marko;
    Publisher: Zenodo
    Project: EC | EMBEDDIA (825153)

    Comment: 8 pages, 3 figures, LREC2020 conference

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  • publication . Preprint . 2020
    Open Access English
    Authors:
    Kasner, Zdeněk; Libovický, Jindřich; Helcl, Jindřich;
    Project: EC | Bergamot (825303)

    Non-autoregressive (nAR) models for machine translation (MT) manifest superior decoding speed when compared to autoregressive (AR) models, at the expense of impaired fluency of their outputs. We improve the fluency of a nAR model with connectionist temporal classificati...

  • publication . Conference object . Preprint . 2019
    Open Access
    Authors:
    Zouhar, Vilém; Bojar, Ondřej;
    Persistent Identifiers
    Project: EC | Bergamot (825303)

    It is not uncommon for Internet users to have to produce a text in a foreign language they have very little knowledge of and areunable to verify the translation quality.We call the task “outbound translation” and explore it by introducing an open-sourcemodular system Pt...

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  • publication . Preprint . Conference object . 2019
    Open Access English
    Authors:
    Jakub Náplava; Milan Straka;
    Project: EC | KHRESMOI (257528)

    Grammatical error correction in English is a long studied problem with many existing systems and datasets. However, there has been only a limited research on error correction of other languages. In this paper, we present a new dataset AKCES-GEC on grammatical error corr...

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  • publication . Preprint . Conference object . 2019
    Open Access English
    Authors:
    Kocmi, Tom; Bojar, Ondřej;
    Persistent Identifiers
    Project: EC | Bergamot (825303)

    Recent progress in neural machine translation is directed towards larger neural networks trained on an increasing amount of hardware resources. As a result, NMT models are costly to train, both financially, due to the electricity and hardware cost, and environmentally, ...

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  • publication . Conference object . Contribution for newspaper or weekly magazine . Preprint . 2019
    Open Access English
    Authors:
    Jindřich Helcl; Jindřich Libovický; Martin Popel;
    Publisher: Association for Computational Linguistics
    Project: EC | Bergamot (825303)

    Comment: WMT19

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  • publication . Contribution for newspaper or weekly magazine . Preprint . Conference object . 2018
    Open Access English
    Authors:
    Jindřich Helcl; Jindřich Libovický;
    Project: EC | QT21 (645452)

    In this paper, we describe our submissions to the WMT17 Multimodal Translation Task. For Task 1 (multimodal translation), our best scoring system is a purely textual neural translation of the source image caption to the target language. The main feature of the system is...

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19 research outcomes, page 1 of 2