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1
Universal Dependencies 2.9
Zeman, Daniel; Nivre, Joakim; Abrams, Mitchell. - : Universal Dependencies Consortium, 2021
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2
Universal Dependencies 2.8.1
Zeman, Daniel; Nivre, Joakim; Abrams, Mitchell. - : Universal Dependencies Consortium, 2021
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3
Universal Dependencies 2.8
Zeman, Daniel; Nivre, Joakim; Abrams, Mitchell. - : Universal Dependencies Consortium, 2021
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4
A Digital Corpus of St. Lawrence Island Yupik ...
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5
Akuzipik/Yupik (St. Lawrence Island, Alaska, USA; Chukotka, Russia) - Language Snapshot ...
Koonooka, Christopher Petuwaq; Schreiner, Sylvia L.R.; Soldati, Giulia Masella. - : Language Documentation and Description, 2021
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6
A digital corpus of St. Lawrence Island Yupik for the Yupik Community
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7
Morphology Matters: A Multilingual Language Modeling Analysis ...
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8
Multidirectional leveraging for computational morphology and language documentation and revitalization
Schreiner, Sylvia L. R.; Schwartz, Lane; Hunt, Benjamin. - : University of Hawaii Press, 2020
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9
Multidirectional leveraging for computational morphology and language documentation and revitalization
Schreiner, Sylvia L. R.; Schwartz, Lane; Hunt, Benjamin. - : University of Hawaii Press, 2020
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10
Community-Focused Language Documentation in Support of Language Education and Revitalization for St. Lawrence Island Yupik
Schwartz, Lane; Schreiner, Sylvia L.R.; Chen, Emily. - : Centre interuniversitaire d’études et de recherches autochtones (CIÉRA), 2019. : Érudit, 2019
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11
Unsupervised Grammar Induction with Depth-bounded PCFG ...
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12
Liinnaqumalghiit: A web-based tool for addressing orthographic transparency in St. Lawrence Island/Central Siberian Yupik
Schwartz, Lane; Chen, Emily. - : University of Hawaii Press, 2017
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13
Liinnaqumalghiit: A web-based tool for addressing orthographic transparency in St. Lawrence Island/Central Siberian Yupik
Schwartz, Lane; Chen, Emily. - : University of Hawaii Press, 2017
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14
Compiling contextualized lists of frequent vocabulary from user- supplied corpora using natural language processing techniques
Abdar, Omid. - 2016
Abstract: Since there are thousands of words to learn in a new language, one common challenge for language learners and teachers is knowing which vocabulary items to prioritize over the others and, in general, setting vocabulary-learning goals. Within vocabulary teaching research, one approach has been to focus on lists of the most common vocabulary. West (1953) proposed a list of the 2000 most frequent word families in English that, it was argued, were most important for learners to master. Along the same lines, Coxhead (2000) offered a list of the most common words in academic English known as the Academic Word List (AWL). Arguing that AWL did not adequately reflect the learners’ specialized vocabulary needs, however, corpus linguists began to develop wordlists in specialized subject areas with an English for Specific Purposes (ESP) perspective for students in Business, Engineering, Medical, and Law majors and so on. A central theme in almost all previous endeavors to develop better wordlists has been the notion of 'representativeness'—the extent to which a wordlist 'represents' the language needs of leaners. In this study, it is proposed that an alternative way to maximize representativeness in a wordlist is to enable users to compile a wordlist from any text or corpus that is of interest to them and to provide the means of compiling a wordlist using that text. Using Natural Language Toolkit (NLTK), this study shows how a few Natural Language Processing (NLP) techniques may be used to compile a list of the most common words in the Europarl corpus along with retrieving example sentences from the corpus for each word. This new approach can have applications for both language leaners as well as for the purposes of preparing instructional materials in an ESP setting.
Keyword: English for Specific Purposes; Natural Language Processing; Vocabulary; Wordlists
URL: http://hdl.handle.net/2142/92955
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15
Better splitting algorithms for parallel corpus processing
In: The Prague bulletin of mathematical linguistics. - Praha : Univ. (2012) 98, 109-119
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16
An incremental syntactic language model for statistical phrase-based translation.
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17
Incremental Syntactic Language Models for Phrase-Based Translation
In: DTIC (2011)
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18
Hierarchical phrase-based grammar extraction in Joshua : suffix arrays and prefix trees
In: The Prague bulletin of mathematical linguistics. - Praha : Univ. (2010) 93, 157-166
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OLC Linguistik
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