  Over 800 languages are spoken across West Africa. Despite the obvious
diversity among people who speak these languages, one language significantly
unifies them all - West African Pidgin English. There are at least 80 million
speakers of West African Pidgin English. However, there is no known natural
language processing (NLP) work on this language. In this work, we perform the
first NLP work on the most popular variant of the language, providing three
major contributions. First, the provision of a Pidgin corpus of over 56000
sentences, which is the largest we know of. Secondly, the training of the first
ever cross-lingual embedding between Pidgin and English. This aligned embedding
will be helpful in the performance of various downstream tasks between English
and Pidgin. Thirdly, the training of an Unsupervised Neural Machine Translation
model between Pidgin and English which achieves BLEU scores of 7.93 from Pidgin
to English, and 5.18 from English to Pidgin. In all, this work greatly reduces
the barrier of entry for future NLP works on West African Pidgin English.
