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Hits 1 – 19 of 19

1
AUTOLEX: An Automatic Framework for Linguistic Exploration ...
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2
Phoneme Recognition through Fine Tuning of Phonetic Representations: a Case Study on Luhya Language Varieties ...
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3
Systematic Inequalities in Language Technology Performance across the World's Languages ...
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4
Evaluating the Morphosyntactic Well-formedness of Generated Texts ...
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5
Evaluating the Morphosyntactic Well-formedness of Generated Texts ...
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6
Lexically Aware Semi-Supervised Learning for OCR Post-Correction ...
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7
When is Wall a Pared and when a Muro? -- Extracting Rules Governing Lexical Selection ...
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8
When is Wall a Pared and when a Muro?: Extracting Rules Governing Lexical Selection ...
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9
Lexically-Aware Semi-Supervised Learning for OCR Post-Correction ...
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10
AlloVera: a multilingual allophone database
In: LREC 2020: 12th Language Resources and Evaluation Conference ; https://halshs.archives-ouvertes.fr/halshs-02527046 ; LREC 2020: 12th Language Resources and Evaluation Conference, European Language Resources Association, May 2020, Marseille, France ; https://lrec2020.lrec-conf.org/ (2020)
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11
AlloVera: A Multilingual Allophone Database ...
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12
Automatic Extraction of Rules Governing Morphological Agreement ...
Abstract: Creating a descriptive grammar of a language is an indispensable step for language documentation and preservation. However, at the same time it is a tedious, time-consuming task. In this paper, we take steps towards automating this process by devising an automated framework for extracting a first-pass grammatical specification from raw text in a concise, human- and machine-readable format. We focus on extracting rules describing agreement, a morphosyntactic phenomenon at the core of the grammars of many of the world's languages. We apply our framework to all languages included in the Universal Dependencies project, with promising results. Using cross-lingual transfer, even with no expert annotations in the language of interest, our framework extracts a grammatical specification which is nearly equivalent to those created with large amounts of gold-standard annotated data. We confirm this finding with human expert evaluations of the rules that our framework produces, which have an average accuracy of 78%. We ... : Accepted at EMNLP 2020 ...
Keyword: Computation and Language cs.CL; FOS Computer and information sciences
URL: https://arxiv.org/abs/2010.01160
https://dx.doi.org/10.48550/arxiv.2010.01160
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13
A Summary of the First Workshop on Language Technology for Language Documentation and Revitalization ...
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14
Universal Phone Recognition with a Multilingual Allophone System ...
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15
X-FACTR: Multilingual Factual Knowledge Retrieval from Pretrained Language Models ...
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16
AlloVera: a multilingual allophone database
In: LREC 2020: 12th Language Resources and Evaluation Conference ; https://halshs.archives-ouvertes.fr/halshs-02527046 ; LREC 2020: 12th Language Resources and Evaluation Conference, European Language Resources Association, May 2020, Marseille, France ; https://lrec2020.lrec-conf.org/ (2020)
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17
Generalized Data Augmentation for Low-Resource Translation ...
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18
Pushing the Limits of Low-Resource Morphological Inflection ...
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19
Should All Cross-Lingual Embeddings Speak English? ...
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