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.

本文介绍了针对西非洋泾浜英语最常用的变体进行的第一项自然语言处理工作，提供了标准语料库、跨语言嵌入和无监督神经机器翻译模型等三个贡献，有效地降低了未来 NLP 工作的准入门槛。

PidginUNMT：从西非皮钦语到英语的无监督神经机器翻译