TLDR: We trained a model that can translate sentences from West African Pidgin (Creole) to English - and vice versa - without showing it a single parallel sentence (a Pidgin sentence and its English equivalent) to learn from. You can skip to the Results section at the end of the article to see some example translations by our model and the link to the code on github. Translation is an important area of research in Artificial Intelligence, and, most of all, communication. Many Machine Translation works have focused on popular languages like English, French, German, Chinese and so on. However, little work has been done on African languages. The creation of an Unsupervised Neural Machine Translation model between Pidgin and English which achieves a BLEU score of 7.93 from Pidgin to English and 5.18 from English to Pidgin on a test set of 2101 sentence pairs. Over 1000 languages are spoken across West and Central Africa, with over 250 of them being Nigerian. This aligned vector will be helpful in the performance of various downstream tasks and transfer of models from English to Pidgin. Despite the obvious diversity amongst these languages, one language significantly unifies them all - Pidgin English. The problems this research addresses are the following: There are over 75 million speakers in Nigeria alone, however, there is no known Natural Language Processing work on this language.
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