Web: http://arxiv.org/abs/2205.02364

May 6, 2022, 1:11 a.m. | Barack Wanjawa (1), Lilian Wanzare (2), Florence Indede (2), Owen McOnyango (2), Lawrence Muchemi (1), Edward Ombui (3) ((1) University of Nairobi Ken

cs.LG updates on arXiv.org arxiv.org

This research developed a Kencorpus Swahili Question Answering Dataset
KenSwQuAD from raw data of Swahili language, which is a low resource language
predominantly spoken in Eastern African and also has speakers in other parts of
the world. Question Answering datasets are important for machine comprehension
of natural language processing tasks such as internet search and dialog
systems. However, before such machine learning systems can perform these tasks,
they need training data such as the gold standard Question Answering (QA) set …

arxiv dataset language question answering

More from arxiv.org / cs.LG updates on arXiv.org

Director, Applied Mathematics & Computational Research Division

@ Lawrence Berkeley National Lab | Berkeley, Ca

Business Data Analyst

@ MainStreet Family Care | Birmingham, AL

Assistant/Associate Professor of the Practice in Business Analytics

@ Georgetown University McDonough School of Business | Washington DC

Senior Data Science Writer

@ NannyML | Remote

Director of AI/ML Engineering

@ Armis Industries | Remote (US only), St. Louis, California

Digital Analytics Manager

@ Patagonia | Ventura, California