Multilingual training of crosslingual word embeddings

Long Duong, Hiroshi Kanayama, Tengfei Ma, Steven Bird, Trevor Cohn

    Research output: Chapter in Book/Report/Conference proceedingConference Paper published in Proceedings

    Abstract

    Crosslingual word embeddings represent lexical items from different languages using the same vector space, enabling crosslingual transfer. Most prior work constructs embeddings for a pair of languages, with English on one side. We investigate methods for building high quality crosslingual word embeddings for many languages in a unified vector space. In this way, we can exploit and combine information from many languages. We report competitive performance on bilingual lexicon induction, monolingual similarity and crosslingual document classification tasks.

    Original languageEnglish
    Title of host publicationLong Papers - Continued
    Place of PublicationValencia, Spain
    PublisherAssociation for Computational Linguistics (ACL)
    Pages894-904
    Number of pages11
    Volume1
    ISBN (Electronic)9781510838604
    Publication statusPublished - 1 Jul 2017
    Event15th Conference of the European Chapter of the Association for Computational Linguistics, EACL 2017 - Valencia, Spain
    Duration: 3 Apr 20177 Apr 2017

    Conference

    Conference15th Conference of the European Chapter of the Association for Computational Linguistics, EACL 2017
    CountrySpain
    CityValencia
    Period3/04/177/04/17

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  • Cite this

    Duong, L., Kanayama, H., Ma, T., Bird, S., & Cohn, T. (2017). Multilingual training of crosslingual word embeddings. In Long Papers - Continued (Vol. 1, pp. 894-904). Association for Computational Linguistics (ACL).