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Modeling Language Variation and Universals: A Survey on Typological Linguistics for Natural Language Processing
In: https://hal.archives-ouvertes.fr/hal-01856176 ; 2018 (2018)
Abstract: Addressing the cross-lingual variation of grammatical structures and meaning categorization is a key challenge for multilingual Natural Language Processing. The lack of resources for the majority of the world's languages makes supervised learning not viable. Moreover, the performance of most algorithms is hampered by language-specific biases and the neglect of informative multilingual data. The discipline of Linguistic Typology provides a principled framework to compare languages systematically and empirically and documents their variation in publicly available databases. These enshrine crucial information to design language-independent algorithms and refine techniques devised to mitigate the above-mentioned issues, including cross-lingual transfer and multilingual joint models, with typological features. In this survey, we demonstrate that typology is beneficial to several NLP applications, involving both semantic and syntactic tasks. Moreover, we outline several techniques to extract features from databases or acquire them automatically: these features can be subsequently integrated into multilingual models to tie parameters together cross-lingually or gear a model towards a specific language. Finally, we advocate for a new typology that accounts for the patterns within individual examples rather than entire languages, and for graded categories rather than discrete ones, in oder to bridge the gap with the contextual and continuous nature of machine learning algorithms.
Keyword: [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]; [INFO.INFO-TT]Computer Science [cs]/Document and Text Processing; [SCCO.COMP]Cognitive science/Computer science; [SCCO.LING]Cognitive science/Linguistics; [SCCO]Cognitive science; [SHS.INFO]Humanities and Social Sciences/Library and information sciences; [SHS.LANGUE]Humanities and Social Sciences/Linguistics; [SHS.STAT]Humanities and Social Sciences/Methods and statistics; Language typology; Machine learning; Natural Language Processing
URL: https://hal.archives-ouvertes.fr/hal-01856176
https://hal.archives-ouvertes.fr/hal-01856176/document
https://hal.archives-ouvertes.fr/hal-01856176/file/1807.00914.pdf
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2
Unsupervised Cross-Lingual Information Retrieval using Monolingual Data Only ...
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3
Unsupervised Cross-Lingual Information Retrieval Using Monolingual Data Only ...
Litschko, Robert; Glavas, Goran; Ponzetto, Simone Paolo. - : Apollo - University of Cambridge Repository, 2018
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4
Modeling Language Variation and Universals: A Survey on Typological Linguistics for Natural Language Processing ...
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5
On the Limitations of Unsupervised Bilingual Dictionary Induction ...
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6
Fully Statistical Neural Belief Tracking ...
Mrkšić, Nikola; Vulić, Ivan. - : arXiv, 2018
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7
Bio-SimVerb ...
Chiu, Hon Wing; Pyysalo, Sampo; Vulic, Ivan. - : Apollo - University of Cambridge Repository, 2018
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8
Scoring Lexical Entailment with a Supervised Directional Similarity Network ...
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9
Adversarial Propagation and Zero-Shot Cross-Lingual Transfer of Word Vector Specialization ...
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10
Post-Specialisation: Retrofitting Vectors of Words Unseen in Lexical Resources ...
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11
Isomorphic Transfer of Syntactic Structures in Cross-Lingual NLP ...
Ponti, Edoardo; Reichart, Roi; Korhonen, Anna-Leena. - : Apollo - University of Cambridge Repository, 2018
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Language Modeling for Morphologically Rich Languages: Character-Aware Modeling for Word-Level Prediction ...
Gerz, Daniela; Vulić, Ivan; Ponti, Edoardo. - : Apollo - University of Cambridge Repository, 2018
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13
A deep learning approach to bilingual lexicon induction in the biomedical domain ...
Heyman, Geert; Vulić, Ivan; Moens, Marie-Francine. - : Apollo - University of Cambridge Repository, 2018
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Injecting Lexical Contrast into Word Vectors by Guiding Vector Space Specialisation ...
Vulic, Ivan; Korhonen, Anna-Leena; Linguist, Assoc Computat. - : Apollo - University of Cambridge Repository, 2018
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15
Investigating the cross-lingual translatability of VerbNet-style classification. ...
Majewska, Olga; Vulić, Ivan; McCarthy, Diana. - : Apollo - University of Cambridge Repository, 2018
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Specialising Word Vectors for Lexical Entailment ...
Vulic, Ivan; Mrk�I?, Nikola. - : Apollo - University of Cambridge Repository, 2018
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A deep learning approach to bilingual lexicon induction in the biomedical domain. ...
Heyman, Geert; Vulić, Ivan; Moens, Marie-Francine. - : Apollo - University of Cambridge Repository, 2018
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18
Post-Specialisation: Retrofitting Vectors of Words Unseen in Lexical Resources ...
Vulic, Ivan; Glavaš, Goran; Mrkšić, Nikola. - : Apollo - University of Cambridge Repository, 2018
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19
A deep learning approach to bilingual lexicon induction in the biomedical domain.
Heyman, Geert; Vulić, Ivan; Moens, Marie-Francine. - : Springer Science and Business Media LLC, 2018. : BMC Bioinformatics, 2018
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20
Language Modeling for Morphologically Rich Languages: Character-Aware Modeling for Word-Level Prediction
Gerz, Daniela; Vulić, Ivan; Ponti, Edoardo. - : MIT Press - Journals, 2018. : Transactions of the Association for Computational Linguistics, 2018
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