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From FreEM to D'AlemBERT ; From FreEM to D'AlemBERT: a Large Corpus and a Language Model for Early Modern French
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In: Proceedings of the 13th Language Resources and Evaluation Conference ; https://hal.inria.fr/hal-03596653 ; Proceedings of the 13th Language Resources and Evaluation Conference, European Language Resources Association, Jun 2022, Marseille, France (2022)
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Hippocampal and auditory contributions to speech segmentation
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In: ISSN: 0010-9452 ; Cortex ; https://hal.archives-ouvertes.fr/hal-03604957 ; Cortex, Elsevier, 2022, ⟨10.1016/j.cortex.2022.01.017⟩ (2022)
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The CLASSLA-StanfordNLP model for morphosyntactic annotation of standard Slovenian 1.3
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FiNER-139: A Financial Numeric Entity Recognition Dataset ...
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FiNER-139: A Financial Numeric Entity Recognition Dataset ...
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Estimating the Emotional Information in Japanese Songs Using Search Engines
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In: Sensors; Volume 22; Issue 5; Pages: 1800 (2022)
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Joint learning of morphology and syntax with cross-level contextual information flow
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In: 2022 ; 1 ; 33 (2022)
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Abstract:
© 2022 The Authors. Published by Cambridge University Press. This is an open access article available under a Creative Commons licence. The published version can be accessed at the following link on the publisher’s website: 10.1017/S1351324921000371 ; We propose an integrated deep learning model for morphological segmentation, morpheme tagging, part-of-speech (POS) tagging, and syntactic parsing onto dependencies, using cross-level contextual information flow for every word, from segments to dependencies, with an attention mechanism at horizontal flow. Our model extends the work of Nguyen and Verspoor (2018) on joint POS tagging and dependency parsing to also include morphological segmentation and morphological tagging. We report our results on several languages. Primary focus is agglutination in morphology, in particular Turkish morphology, for which we demonstrate improved performance compared to models trained for individual tasks. Being one of the earlier efforts in joint modeling of syntax and morphology along with dependencies, we discuss prospective guidelines for future comparison. ; This research has been supported by Scientific and Technological Research Council of Turkey (TUBITAK), project number EEEAG-115E464.
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Keyword:
attention; deep learning; dependency parsing; morphological segmentation; morphological tagging; morphology; recurrent neural networks; syntax
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URL: http://hdl.handle.net/2436/624440 https://doi.org/10.1017/S1351324921000371
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Corpus Linguistics approaches to trainee translators’ framing practice in news translation
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In: Translation and Interpreting : the International Journal of Translation and Interpreting Research, Vol 12 , Iss 1 (2022) (2022)
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Dissociated face- and word-selective intracerebral responses in the human ventral occipito-temporal cortex
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In: ISSN: 1863-2653 ; EISSN: 1863-2661 ; Brain Structure and Function ; https://hal.archives-ouvertes.fr/hal-03437752 ; Brain Structure and Function, Springer Verlag, 2021, 226 (9), pp.3031-3049. ⟨10.1007/s00429-021-02350-4⟩ (2021)
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Critical information thresholds underlying generic and familiar face categorisation at the same face encounter
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In: ISSN: 1053-8119 ; EISSN: 1095-9572 ; NeuroImage ; https://hal.archives-ouvertes.fr/hal-03437754 ; NeuroImage, Elsevier, 2021, 243, pp.118481. ⟨10.1016/j.neuroimage.2021.118481⟩ (2021)
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Exploring the Relationship Between Different Smartphone Reading Annotation Strategies and Students’ Comprehension
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In: Boise State University Theses and Dissertations (2021)
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Oscillatory activity and EEG phase synchrony of concurrent word segmentation and meaning-mapping in 9-year-old children
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In: ISSN: 1878-9293 ; EISSN: 1878-9307 ; Developmental Cognitive Neuroscience ; https://hal.archives-ouvertes.fr/hal-03334735 ; Developmental Cognitive Neuroscience, Elsevier, 2021, 51, pp.101010. ⟨10.1016/j.dcn.2021.101010⟩ (2021)
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From Error Annotation to Quantitative Analysis: Patterns in Russian Language Learning
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In: ISSN: 0036-0252 ; Russian language journal ; https://hal.archives-ouvertes.fr/hal-03376956 ; Russian language journal, American Councils for International Education, Michigan State University 2021, 71 (3), pp.39-70 (2021)
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Hierarchical-Task Reservoir for Online Semantic Analysis from Continuous Speech
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In: ISSN: 2162-237X ; IEEE Transactions on Neural Networks and Learning Systems ; https://hal.inria.fr/hal-03031413 ; IEEE Transactions on Neural Networks and Learning Systems, IEEE, 2021, ⟨10.1109/TNNLS.2021.3095140⟩ ; https://ieeexplore.ieee.org/abstract/document/9548713/metrics#metrics (2021)
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Corpus and Models for Lemmatisation and POS-tagging of Classical French Theatre
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In: EISSN: 2416-5999 ; Journal of Data Mining and Digital Humanities ; https://halshs.archives-ouvertes.fr/halshs-02591388 ; Journal of Data Mining and Digital Humanities, Episciences.org, 2021, ⟨10.46298/jdmdh.6485⟩ (2021)
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Corpus and Models for Lemmatisation and POS-tagging of Old French
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In: https://halshs.archives-ouvertes.fr/halshs-03353125 ; 2021 (2021)
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Old Catalan Morphosyntax: developing an annotated corpus
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In: EISSN: 2059-481X ; Journal of Open Humanities Data ; https://hal.archives-ouvertes.fr/hal-03617737 ; Journal of Open Humanities Data, Ubiquity Press, 2021, 7, pp.30. ⟨10.5334/johd.54⟩ (2021)
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Automated audio captioning by fine-tuning bart with audioset tags
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In: DCASE 2021 - 6th Workshop on Detection and Classification of Acoustic Scenes and Events ; https://hal.inria.fr/hal-03522488 ; DCASE 2021 - 6th Workshop on Detection and Classification of Acoustic Scenes and Events, Nov 2021, Virtual, Spain (2021)
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