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Publication . Conference object . Article . Preprint . 2020

Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages

Wilhelmina Nekoto; Vukosi Marivate; Tshinondiwa Matsila; Timi E. Fasubaa; Tajudeen Kolawole; Taiwo Fagbohungbe; Solomon Oluwole Akinola; +41 Authors
Open Access
Published: 05 Oct 2020
Publisher: Association for Computational Linguistics
Country: United Kingdom

Research in NLP lacks geographic diversity, and the question of how NLP can be scaled to low-resourced languages has not yet been adequately solved. "Low-resourced"-ness is a complex problem going beyond data availability and reflects systemic problems in society. In this paper, we focus on the task of Machine Translation (MT), that plays a crucial role for information accessibility and communication worldwide. Despite immense improvements in MT over the past decade, MT is centered around a few high-resourced languages. As MT researchers cannot solve the problem of low-resourcedness alone, we propose participatory research as a means to involve all necessary agents required in the MT development process. We demonstrate the feasibility and scalability of participatory research with a case study on MT for African languages. Its implementation leads to a collection of novel translation datasets, MT benchmarks for over 30 languages, with human evaluations for a third of them, and enables participants without formal training to make a unique scientific contribution. Benchmarks, models, data, code, and evaluation results are released under

Comment: Findings of EMNLP 2020; updated benchmarks

Subjects by Vocabulary

Microsoft Academic Graph classification: Focus (linguistics) Data science Task (project management) Participatory action research Languages of Africa Machine translation computer.software_genre computer Process (engineering) Computer science


Computation and Language (cs.CL), Artificial Intelligence (cs.AI), Machine Learning (cs.LG), FOS: Computer and information sciences, Computer Science - Computation and Language, Computer Science - Artificial Intelligence, Computer Science - Machine Learning

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