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Found 7 papers, 6 papers with code
Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages
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.
MasakhaNER: Named Entity Recognition for African Languages
We take a step towards addressing the under-representation of the African continent in NLP research by creating the first large publicly available high-quality dataset for named entity recognition (NER) in ten African languages, bringing together a variety of stakeholders.
HausaMT v1.0: Towards English--Hausa Neural Machine Translation
Neural Machine Translation (NMT) for low-resource languages suffers from low performance because of the lack of large amounts of parallel data and language diversity.
NASS-AI: Towards Digitization of Parliamentary Bills using Document Level Embedding and Bidirectional Long Short-Term Memory
In this paper, we present results from ongoing research on the categorization of bills introduced in the Nigerian parliament since the fourth republic (1999 - 2018).
Optical Character Recognition
Optical Character Recognition (OCR)
Predicting and Analyzing Law-Making in Kenya
Modelling and analyzing parliamentary legislation, roll-call votes and order of proceedings in developed countries has received significant attention in recent years.
HausaMT v1.0: Towards English-Hausa Neural Machine Translation
Neural Machine Translation (NMT) for low-resource languages suffers from low performance because of the lack of large amounts of parallel data and language diversity.
