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AUTOLEX: An Automatic Framework for Linguistic Exploration ...
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When Being Unseen from mBERT is just the Beginning: Handling New Languages With Multilingual Language Models
In: NAACL-HLT 2021 - 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies ; https://hal.inria.fr/hal-03251105 ; NAACL-HLT 2021 - 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Jun 2021, Mexico City, Mexico (2021)
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SD-QA: Spoken Dialectal Question Answering for the Real World ...
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SD-QA: Spoken Dialectal Question Answering for the Real World ...
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Phoneme Recognition through Fine Tuning of Phonetic Representations: a Case Study on Luhya Language Varieties ...
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Machine Translation into Low-resource Language Varieties ...
Abstract: State-of-the-art machine translation (MT) systems are typically trained to generate the "standard" target language; however, many languages have multiple varieties (regional varieties, dialects, sociolects, non-native varieties) that are different from the standard language. Such varieties are often low-resource, and hence do not benefit from contemporary NLP solutions, MT included. We propose a general framework to rapidly adapt MT systems to generate language varieties that are close to, but different from, the standard target language, using no parallel (source--variety) data. This also includes adaptation of MT systems to low-resource typologically-related target languages. We experiment with adapting an English--Russian MT system to generate Ukrainian and Belarusian, an English--Norwegian Bokmål system to generate Nynorsk, and an English--Arabic system to generate four Arabic dialects, obtaining significant improvements over competitive baselines. ... : The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (ACL-IJCNLP 2021) ...
Keyword: Computation and Language cs.CL; FOS Computer and information sciences
URL: https://arxiv.org/abs/2106.06797
https://dx.doi.org/10.48550/arxiv.2106.06797
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7
Code to Comment Translation: A Comparative Study on Model Effectiveness & Errors ...
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8
Systematic Inequalities in Language Technology Performance across the World's Languages ...
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9
Multilingual Code-Switching for Zero-Shot Cross-Lingual Intent Prediction and Slot Filling ...
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10
Investigating Post-pretraining Representation Alignment for Cross-Lingual Question Answering ...
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11
Towards More Equitable Question Answering Systems: How Much More Data Do You Need? ...
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12
Cross-Lingual Text Classification of Transliterated Hindi and Malayalam ...
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13
Evaluating the Morphosyntactic Well-formedness of Generated Texts ...
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14
Evaluating the Morphosyntactic Well-formedness of Generated Texts ...
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15
Towards more equitable question answering systems: How much more data do you need? ...
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16
Lexically Aware Semi-Supervised Learning for OCR Post-Correction ...
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17
When is Wall a Pared and when a Muro? -- Extracting Rules Governing Lexical Selection ...
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18
When is Wall a Pared and when a Muro?: Extracting Rules Governing Lexical Selection ...
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19
Lexically-Aware Semi-Supervised Learning for OCR Post-Correction ...
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20
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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