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Empirical Evaluation of Sequence-to-Sequence Models for Word Discovery in Low-resource Settings
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In: Interspeech 2019 ; https://hal.archives-ouvertes.fr/hal-02193867 ; Interspeech 2019, Sep 2019, Graz, Austria (2019)
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Unsupervised Compositionality Prediction of Nominal Compounds
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In: ISSN: 0891-2017 ; EISSN: 1530-9312 ; Computational Linguistics ; https://hal.archives-ouvertes.fr/hal-02318196 ; Computational Linguistics, Massachusetts Institute of Technology Press (MIT Press), 2019, 45 (1), pp.1-57. ⟨10.1162/coli_a_00341⟩ (2019)
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How Does Language Influence Documentation Workflow? Unsupervised Word Discovery Using Translations in Multiple Languages
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In: Journées Scientifiques du Groupement de Recherche: Linguistique Informatique, Formelle et de Terrain (LIFT). ; https://hal.archives-ouvertes.fr/hal-02895895 ; Journées Scientifiques du Groupement de Recherche: Linguistique Informatique, Formelle et de Terrain (LIFT)., Nov 2019, Orléans, France (2019)
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How Does Language Influence Documentation Workflow? Unsupervised Word Discovery Using Translations in Multiple Languages ...
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CogniVal: A Framework for Cognitive Word Embedding Evaluation
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In: Proceedings of the 23rd Conference on Computational Natural Language Learning (CoNLL) (2019)
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Unsupervised Compositionality Prediction of Nominal Compounds
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