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SemEval-2022 Task 2: Multilingual Idiomaticity Detection and Sentence Embedding ...
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Improving Tokenisation by Alternative Treatment of Spaces ...
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Investigating alignment interpretability for low-resource NMT
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In: ISSN: 0922-6567 ; EISSN: 1573-0573 ; Machine Translation ; https://hal.archives-ouvertes.fr/hal-03139744 ; Machine Translation, Springer Verlag, 2021, ⟨10.1007/s10590-020-09254-w⟩ (2021)
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AStitchInLanguageModels: Dataset and Methods for the Exploration of Idiomaticity in Pre-Trained Language Models ...
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Unsupervised Word Segmentation from Discrete Speech Units in Low-Resource Settings ...
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Assessing the Representations of Idiomaticity in Vector Models with a Noun Compound Dataset Labeled at Type and Token Levels ...
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The Role of negative information when learning dense word vectors ; O papel da informação negativa na aprendizagem de vetores palavra densos
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Investigating Language Impact in Bilingual Approaches for Computational Language Documentation
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In: Proceedings of the 1st Joint SLTU and CCURL Workshop (SLTU-CCURL 2020), ; SLTU-CCURL workshop, LREC 2020 ; https://hal.archives-ouvertes.fr/hal-02895907 ; SLTU-CCURL workshop, LREC 2020, May 2020, Marseille, France (2020)
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Annotated corpora and tools of the PARSEME Shared Task on Semi-Supervised Identification of Verbal Multiword Expressions (edition 1.2)
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Investigating Language Impact in Bilingual Approaches for Computational Language Documentation ...
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Abstract:
For endangered languages, data collection campaigns have to accommodate the challenge that many of them are from oral tradition, and producing transcriptions is costly. Therefore, it is fundamental to translate them into a widely spoken language to ensure interpretability of the recordings. In this paper we investigate how the choice of translation language affects the posterior documentation work and potential automatic approaches which will work on top of the produced bilingual corpus. For answering this question, we use the MaSS multilingual speech corpus (Boito et al., 2020) for creating 56 bilingual pairs that we apply to the task of low-resource unsupervised word segmentation and alignment. Our results highlight that the choice of language for translation influences the word segmentation performance, and that different lexicons are learned by using different aligned translations. Lastly, this paper proposes a hybrid approach for bilingual word segmentation, combining boundary clues extracted from a ... : Accepted to 1st Joint SLTU and CCURL Workshop ...
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Keyword:
Computation and Language cs.CL; FOS Computer and information sciences
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URL: https://dx.doi.org/10.48550/arxiv.2003.13325 https://arxiv.org/abs/2003.13325
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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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A small Griko-Italian speech translation corpus
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In: 6th international workshop on spoken language technologies for under-resourced languages(SLTU'18) ; https://hal.archives-ouvertes.fr/hal-01962528 ; 6th international workshop on spoken language technologies for under-resourced languages(SLTU'18), Aug 2018, New Delhi, India (2018)
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Unsupervised Word Segmentation from Speech with Attention
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In: Interspeech 2018 ; https://hal.archives-ouvertes.fr/hal-01818092 ; Interspeech 2018, Sep 2018, Hyderabad, India (2018)
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Language, Cognition, and Computational Models
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In: https://hal.archives-ouvertes.fr/hal-01722351 ; Cambridge University Press, 2018 ; https://www.cambridge.org/core/books/language-cognition-and-computational-models/90CC7DBA6CADB1FE361266D311CB4413 (2018)
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