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Towards Supervised and Unsupervised Neural Machine Translation Baselines for Nigerian Pidgin

2020/03/27 by Ahia, Orevaoghene, Ogueji, Kelechi · 1 citation
#Computation and Language (cs.CL) #FOS: Computer and information sciences #Machine Learning (cs.LG)

paper · doi:10.48550/arxiv.2003.12660

Abstract

Nigerian Pidgin is arguably the most widely spoken language in Nigeria. Variants of this language are also spoken across West and Central Africa, making it a very important language. This work aims to establish supervised and unsupervised neural machine translation (NMT) baselines between English and Nigerian Pidgin. We implement and compare NMT models with different tokenization methods, creating a solid foundation for future works.

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