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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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Study of non-projective dependencies in French ; Étude des dépendances syntaxiques non projectives en français
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In: ISSN: 1248-9433 ; EISSN: 1965-0906 ; Revue TAL ; https://hal.inria.fr/hal-03389157 ; Revue TAL, ATALA (Association pour le Traitement Automatique des Langues), 2021, 62 (1) (2021)
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To be or not to be adultlike in syntax: An experimental study of language acquisition and processing in children ...
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Syntax-semantics interactions – seeking evidence from a synchronic analysis of 38 languages [version 1; peer review: 1 approved] ...
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Syntax-semantics interactions – seeking evidence froma synchronic analysis of 38 languages: scripts repository ...
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Syntax-semantics interactions – seeking evidence froma synchronic analysis of 38 languages: dataset repository ...
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Syntax-semantics interactions – seeking evidence froma synchronic analysis of 38 languages: dataset repository ...
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Syntax-semantics interactions – seeking evidence froma synchronic analysis of 38 languages: scripts repository ...
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Syntax-semantics interactions – seeking evidence froma synchronic analysis of 38 languages: scripts repository ...
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To be or not to be adultlike in syntax: An experimental study of language acquisition and processing in children
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Syntax-semantics interactions – seeking evidence from a synchronic analysis of 38 languages [version 1; peer review: 1 approved]
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Dependency Syntax in the Automatic Detection of Irony and Stance
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Using Dependency Syntax-Based Methods for Automatic Detection of Psychiatric Comorbidities
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In: Resources and ProcessIng of linguistic, para-linguistic and extra-linguistic Data from people with various forms of cognitive/psychiatric/developmental impairments ; https://hal-imt-atlantique.archives-ouvertes.fr/hal-02861753 ; Resources and ProcessIng of linguistic, para-linguistic and extra-linguistic Data from people with various forms of cognitive/psychiatric/developmental impairments, May 2020, Marseille, France. pp.142-150 ; https://spraakbanken.gu.se/en/rapid-2020 (2020)
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