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1
MasakhaNER: Named entity recognition for African languages
In: EISSN: 2307-387X ; Transactions of the Association for Computational Linguistics ; https://hal.inria.fr/hal-03350962 ; Transactions of the Association for Computational Linguistics, The MIT Press, 2021, ⟨10.1162/tacl⟩ (2021)
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2
The national corpus of contemporary Welsh, 2016-2020 ...
Knight, Dawn; Morris, Steve; Fitzpatrick, Tess. - : UK Data Service, 2021
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3
CorCenCC: Corpws Cenedlaethol Cymraeg Cyfoes – the National Corpus of Contemporary Welsh ...
Knight, Dawn; Morris, Steve; Fitzpatrick, Tess. - : Cardiff University, 2020
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4
Igbo-English Machine Translation:An Evaluation Benchmark
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5
Participatory Research for Low-resourced Machine Translation:A Case Study in African Languages
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6
Igbo-English Machine Translation:An Evaluation Benchmark
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7
Infrastructure for Semantic Annotation in the Genomics Domain
El-Haj, Mahmoud; Rutherford, Nathan; Coole, Matthew. - : European Language Resources Association (ELRA), 2020
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8
Toward an effective Igbo part-of-speech tagger
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9
Corpus-based approaches to Igbo diacritic restoration
Ezeani, Ignatius. - : University of Sheffield, 2019
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10
Open Welsh Language Resources for a Corpus Annotation Framework
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11
Leveraging Pre-Trained Embeddings for Welsh Taggers
Ezeani, Ignatius; Piao, Scott; Neale, Steven; Rayson, Paul; Knight, Dawn. - : Association for Computational Linguistics, 2019
Abstract: While the application of word embedding models to downstream Natural Language Processing (NLP) tasks has been shown to be successful, the benefits for low-resource languages is somewhat limited due to lack of adequate data for training the models. However, NLP research efforts for low-resource languages have focused on constantly seeking ways to harness pre-trained models to improve the performance of NLP systems built to process these languages without the need to re-invent the wheel. One such language is Welsh and therefore, in this paper, we present the results of our experiments on learning a simple multi-task neural network model for part-of-speech and semantic tagging for Welsh using a pre-trained embedding model from FastText. Our model’s performance was compared with those of the existing rule-based stand-alone taggers for part-of-speech and semantic taggers. Despite its simplicity and capacity to perform both tasks simultaneously, our tagger compared very well with the existing taggers.
URL: https://eprints.lancs.ac.uk/id/eprint/135950/
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12
Corpus-Based Approaches to Igbo Diacritic Restoration
Ezeani, Ignatius. - : University of Sheffield, 2019. : Computer Science (Sheffield), 2019
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13
Multi-task projected embedding for igbo
Ezeani, Ignatius; Hepple, Mark; Onyenwe, Ikechukwu. - : Springer-Verlag, 2018
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