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Found 7 papers, 3 papers with code
Findings of the 2021 Conference on Machine Translation (WMT21)
This paper presents the results of the newstranslation task, the multilingual low-resourcetranslation for Indo-European languages, thetriangular translation task, and the automaticpost-editing task organised as part of the Con-ference on Machine Translation (WMT) 2021. In the news task, participants were asked tobuild machine translation systems for any of10 language pairs, to be evaluated on test setsconsisting mainly of news stories.
Machine Intelligence in Africa: a survey
In the last 5 years, the availability of large audio datasets in African countries has opened unlimited opportunities to build machine intelligence (MI) technologies that are closer to the people and speak, learn, understand, and do businesses in local languages, including for those who cannot read and write.
MasakhaPOS: Part-of-Speech Tagging for Typologically Diverse African Languages
In this paper, we present MasakhaPOS, the largest part-of-speech (POS) dataset for 20 typologically diverse African languages.
MasakhaNER 2.0: Africa-centric Transfer Learning for Named Entity Recognition
African languages are spoken by over a billion people, but are underrepresented in NLP research and development.
A Few Thousand Translations Go a Long Way! Leveraging Pre-trained Models for African News Translation
We focus on two questions: 1) How can pre-trained models be used for languages not included in the initial pre-training?
Domain-specific MT for Low-resource Languages: The case of Bambara-French
Translating to and from low-resource languages is a challenge for machine translation (MT) systems due to a lack of parallel data.
Neural Machine Translation for Extremely Low-Resource African Languages: A Case Study on Bambara
Low-resource languages present unique challenges to (neural) machine translation.
