Engage Africa NLP
The App
Leveraging Technology to Support Low-Resourced African Languages
Mission
The Engage Africa NLP initiative is a project designed to foster accessibility and use of African languages in the digital realm through the power of NLP and ML.
This program aims to harness the expertise of language experts, native speakers, translators and technologists to develop tools and applications focusing on low-resourced, underrepresented African languages, with an initial focus on Cameroonian languages.
Initial focus on Cameroonian languages
Execution
By gathering diverse linguistic data, we want to help AI serve not just major languages but also those traditionally overlooked such as Ghɔmálá’, Fulfulde, Ewondo, Duala, Bassa, Bulu, Fe’fe’, Kom, Medumba, Yemba, Ewondo, Bamum, Pinyin, Ngiemboon, Meta’, Nso’, Toupouri, Cameroon Pidgin, Camfranglais and more.
The Engage Africa NLP app is now available on both the App Store and the Play Store.
We are currently using the data collection features of the platform to collect linguistic data and build bilingual corpus between English and each language in order to build the tech.
Subsequently, the platform will evolve to host the tools and tech obtained by training the model.
Everyone can help! Please contribute data, provide feedback, suggest a language focus or click around to find the Request a Translation menu, and give us some work to do.
-
Apple App Store (iOS): Engage Africa NLP on Apple App Store
-
Google Play Store (Android): Engage Africa NLP on Google Play Store
This app will evolve to include the tech built using the data collected.
Time Frame: 1 year
Vision
The data collection platform is the cornerstone of our efforts, designed to gamify the process of linguistic data gathering.
By engaging professional translators, data collectors and native speakers in fun and interactive tasks, we are compiling and valuable dataset that forms the foundation for all subsequent technological developments.
This approach not only accelerates data collection but also ensures the inclusivity and authenticity of the linguistic information gathered.