Contextual neural model for translating bilingual multi-speaker conversations

Sameen Maruf, André F. T. Martins, Gholamreza Haffari

    Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

    Abstract

    Recent works in neural machine translation have begun to explore document translation. However, translating online multi-speaker conversations is still an open problem. In this work, we propose the task of translating Bilingual Multi-Speaker Conversations, and explore neural architectures which exploit both source and target-side conversation histories for this task. To initiate an evaluation for this task, we introduce datasets extracted from Europarl v7 and OpenSubtitles2016. Our experiments on four language-pairs confirm the significance of leveraging conversation history, both in terms of BLEU and manual evaluation.
    Original languageEnglish
    Title of host publicationWMT 2018 - Third Conference on Machine Translation - Proceedings of the Conference
    Subtitle of host publicationOctober 31 - November 1, 2018 Brussels, Belgium
    EditorsOndˇrej Bojar, Rajen Chatterjee, Christian Federmann, Yvette Graham, Barry Haddow, Matthias Huck, Antonio Jimeno Yepes, Philipp Koehn, Christof Monz, Matteo Negri, Aurélie Névéol, Mariana Neves, Matt Post, Lucia Specia, Marco Turchi, Karin Verspoor, Mark Fishel
    Place of PublicationStroudsburg PA USA
    PublisherAssociation for Computational Linguistics (ACL)
    Pages101-112
    Number of pages12
    ISBN (Electronic)9781948087810
    Publication statusPublished - 2018
    EventConference on Machine Translation - Brussels, Belgium
    Duration: 31 Oct 20181 Nov 2018
    Conference number: 3rd
    http://www.statmt.org/wmt18/

    Conference

    ConferenceConference on Machine Translation
    Abbreviated titleWMT 2018
    Country/TerritoryBelgium
    CityBrussels
    Period31/10/181/11/18
    Internet address

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