Machine Translation for African Languages: Community Creation of Datasets and Models in Uganda

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dc.contributor.authorAkera, Benjamin
dc.contributor.authorMukiibi, Jonathan
dc.contributor.authorSanyu Naggayi, Lydia
dc.contributor.authorBabirye, Claire
dc.contributor.authorOwomugisha, Isaac
dc.contributor.authorNsumba, Solomon
dc.contributor.authorNakatumba-Nabende, Joyce
dc.contributor.authorBainomugisha, Engineer
dc.contributor.authorMwebaze, Ernest
dc.contributor.authorQuinn, John
dc.date.accessioned2022-12-29T13:20:32Z
dc.date.available2022-12-29T13:20:32Z
dc.date.issued2022
dc.description.abstractReliable machine translation systems are only available for a small proportion of the world’s languages, the key limitation being a shortage of training and evaluation data. We provide a case study in the creation of such resources by NLP teams who are local to the communities in which these languages are spoken. A parallel text corpus, SALT, was created for five Ugandan languages (Luganda, Runyankole, Acholi, Lugbara and Ateso) and various methods were explored to train and evaluate translation models. The resulting models were found to be effective for practical translation applications, even for those languages with no previous NLP data available, achieving mean BLEU score of 26.2 for translations to English, and 19.9 from English. The SALT dataset and models described are publicly available aten_US
dc.identifier.citationAkera, B., Mukiibi, J., Naggayi, L. S., Babirye, C., Owomugisha, I., Nsumba, S., ... & Quinn, J. (2022, March). Machine Translation For African Languages: Community Creation Of Datasets And Models In Uganda. In 3rd Workshop on African Natural Language Processing.en_US
dc.identifier.urihttps://openreview.net/forum?id=BK-z5qzEU-9
dc.identifier.urihttps://nru.uncst.go.ug/handle/123456789/6744
dc.language.isoenen_US
dc.publishern African Natural Language Processingen_US
dc.titleMachine Translation for African Languages: Community Creation of Datasets and Models in Ugandaen_US
dc.typeOtheren_US
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