Africa has over 2000 languages. Despite this, African languages account for a
small portion of available resources and publications in Natural Language
Processing (NLP). This is due to multiple factors, including: a lack of focus
from government and funding, discoverability, a lack of community, sheer
language complexity, difficulty in reproducing papers and no benchmarks to
compare techniques. To begin to address the identified problems, MASAKHANE, an
open-source, continent-wide, distributed, online research effort for machine
translation for African languages, was founded. In this paper, we discuss our
methodology for building the community and spurring research from the African
continent, as well as outline the success of the community in terms of
addressing the identified problems affecting African NLP.

本文介绍了 MASAKHANE 建立非洲自然语言处理和机器翻译社区的方法和成功经验。