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Over 800 languages are spoken across West Africa. Despite the obviousdiversity among people who speak these languages, one language significantlyunifies them all - West African Pidgin English. There are at least 80 millionspeakers of West African Pidgin English. However, there is no known naturallanguage processing (NLP) work on this language. In this work, we perform thefirst NLP work on the most popular variant of the language, providing threemajor contributions. First, the provision of a Pidgin corpus of over 56000sentences, which is the largest we know of. Secondly, the training of the firstever cross-lingual embedding between Pidgin and English. This aligned embeddingwill be helpful in the performance of various downstream tasks between Englishand Pidgin. Thirdly, the training of an Unsupervised Neural Machine Translationmodel between Pidgin and English which achieves BLEU scores of 7.93 from Pidginto English, and 5.18 from English to Pidgin. In all, this work greatly reducesthe barrier of entry for future NLP works on West African Pidgin English.

PidginUNMT: Unsupervised Neural Machine Translation from West African Pidgin to English