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    Creating Expert Knowledge by Relying on Language Learners: a Generic Approach for Mass-Producing Language Resources by Combining Implicit Crowdsourcing and Language Learning


    Nicolas, Lionel and Lyding, Verena and Borg, Claudia and Forascu, Corina and Fort, Karen and Zdravkova, Katerina and Kosem, Iztok and Cibej, Jaka and Holdt, Spela Arhar and Millour, Alice and König, Alexander and Rodosthenous, Christos and Federico, Sangati and Hasan, Umair ul and Katinskaia, Anisia and Barreiro, Anabela and Aparaschivei, Lavinia and HaCohen-Kerner, Yaakov (2020) Creating Expert Knowledge by Relying on Language Learners: a Generic Approach for Mass-Producing Language Resources by Combining Implicit Crowdsourcing and Language Learning. Proceedings of the 12th Conference on Language Resources and Evaluation (LREC 2020). pp. 268-278.

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    Abstract

    We introduce in this paper a generic approach to combine implicit crowdsourcing and language learning in order to mass-produce language resources (LRs) for any language for which a crowd of language learners can be involved. We present the approach by explaining its core paradigm that consists in pairing specific types of LRs with specific exercises, by detailing both its strengths and challenges, and by discussing how much these challenges have been addressed at present. Accordingly, we also report on on-going proof-of-concept efforts aiming at developing the first prototypical implementation of the approach in order to correct and extend an LR called ConceptNet based on the input crowdsourced from language learners. We then present an international network called the European Network for Combining Language Learning with Crowdsourcing Techniques (enetCollect) that provides the context to accelerate the implementation of the generic approach. Finally, we exemplify how it can be used in several language learning scenarios to produce a multitude of NLP resources and how it can therefore alleviate the long-standing NLP issue of the lack of LRs.

    Item Type: Article
    Keywords: Crowdsourcing; Computer-Assisted Language Learning; Collaborative Resource Construction; COST Action;
    Academic Unit: Faculty of Social Sciences > School of Business
    Item ID: 16005
    Depositing User: Souleiman Hasan
    Date Deposited: 25 May 2022 11:12
    Journal or Publication Title: Proceedings of the 12th Conference on Language Resources and Evaluation (LREC 2020)
    Publisher: European Language Resources Association (ELRA)
    Refereed: Yes
    URI:

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