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Mention Flags (MF): Constraining Transformer-based Text Generators ...
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Agent-Based Modeling of the Evolution of Vowel Harmony
In: North East Linguistics Society (2020)
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VnCoreNLP: A Vietnamese Natural Language Processing Toolkit ...
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Morphological features of the Irish universal dependency treebank
In: Lynn, Teresa, Foster, Jennifer orcid:0000-0002-7789-4853 and Dras, Mark (2017) Morphological features of the Irish universal dependency treebank. In: 15th International Workshop on Treebanks and Linguistic Theories (TLT15), 20-21 Jan 2017, Bloomington, IN, USA. (2017)
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5
CoNLL 2017 Shared Task System Outputs
Zeman, Daniel; Potthast, Martin; Straka, Milan. - : Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL), 2017
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6
Morphological features of the Irish Universal Dependency Treebank
Lynn, Teresa; Foster, Jennifer; Dras, Mark. - : Germany : Rheinisch-Westfaelische Technische Hochschule Aachen, 2017
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7
Multilingual native language identification
Malmasi, Shervin; Dras, Mark. - : Cambridge University Press, 2017
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8
From Word Segmentation to POS Tagging for Vietnamese ...
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9
Modeling Language Change in Historical Corpora: The Case of Portuguese ...
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10
Location mention detection in tweets and microblogs
Malmasi, Shervin; Dras, Mark. - : Singapore : Springer, 2016
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11
Arabic Dialect Identification using a Parallel Multidialectal Corpus
Malmasi, Shervin; Refaee, Eshrag; Dras, Mark. - : Singapore : Springer, 2016
Abstract: We present a study on sentence-level Arabic Dialect Identification using the newly developed Multidialectal Parallel Corpus of Arabic (MPCA) – the first experiments on such data. Using a set of surface features based on characters and words, we conduct three experiments with a linear Support Vector Machine classifier and a meta-classifier using stacked generalization – a method not previously applied for this task. We first conduct a 6-way multi-dialect classification task in the first experiment, achieving 74% accuracy against a random baseline of 16.7% and demonstrating that meta-classifiers can large performance increases over single classifiers. The second experiment investigates pairwise binary dialect classification within the corpus, yielding results as high as 94%, but also highlighting poorer results between closely related dialects such as Palestinian and Jordanian (76%). Our final experiment conducts cross-corpus evaluation on the widely used Arabic Online Commentary (AOC) dataset and demonstrates that despite differing greatly in size and content, models trained with the MPCA generalize to the AOC, and vice versa. Using only 2, 000 sentences from the MPCA, we classify over 26 k sentences from the radically different AOC dataset with 74% accuracy. We also use this data to classify a new dataset of MSA and Egyptian Arabic tweets with 97% accuracy. We find that character n-g are a very informative feature for this task, in both within- and cross-corpus settings. Contrary to previous results, they outperform word n-grams in several experiments here. Several directions for future work are outlined. ; 19 page(s)
URL: http://hdl.handle.net/1959.14/1058267
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12
Automatic Language Identification for Persian and Dari texts
Malmasi, Shervin; Dras, Mark. - : Bali, Indonesia : Pacific Association for Computational Linguistics, 2015
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13
Large-scale Native Language Identification with cross-corpus evaluation
Malmasi, Shervin; Dras, Mark. - : Red Hook, New York : The Association for Computational Linguistics, 2015
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14
Evaluating human pairwise preference judgments
Dras, Mark. - : MIT Press, 2015
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15
Cognate identification using machine translation
Malmasi, Shervin; Dras, Mark. - : Melbourne, Australia : Association for Computational Linguistics, 2015
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Language identification using classifier ensembles
Malmasi, Shervin; Dras, Mark. - : Melbourne, Australia : Association for Computational Linguistics, 2015
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17
Oracle and human baselines for native language identification
Malmasi, Shervin; Tetreault, Joel; Dras, Mark. - : Red Hook, New York : The Association for Computational Linguistics, 2015
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18
Cross-lingual transfer parsing for low-resourced languages: an Irish case study
In: Lynn, Teresa, Foster, Jennifer orcid:0000-0002-7789-4853 , Dras, Mark orcid:0000-0001-9908-7182 and Tounsi, Lamia (2014) Cross-lingual transfer parsing for low-resourced languages: an Irish case study. In: First Celtic Language Technology Workshop, 23 Aug 2014, Dublin, Ireland. (2014)
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Chinese Native Language Identification
Malmasi, Shervin; Dras, Mark. - : Stroudsburg, PA, USA : Association for Computational Linguistics, 2014
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Arabic Native Language Identification
Malmasi, Shervin; Dras, Mark. - : Stroudsburg, PA, USA : Association for Computational Linguistics, 2014
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