Empowering African Languages Through Machine Translation and Artificial Intelligence
Thanks to their artificial potential – deep learning AI and machine translation – it appears that African indigenous languages, several of which fit the description of low-resource and endangered, are set to profit. Artificial Intelligence (AI) technologies, including voice recognition software, natural language processing (NLP), and neural machine translation (NMT), give inventive strategies for documenting, recording and reviving endangered languages in a continent that boasts of over 2,000 spoken languages. Projects such as Mozilla’s Common Voice and the Masakhane project demonstrate the role that collaborative efforts in communities can play in developing AI models that are linguistically appropriate for African languages. This paper explores how AI powered solutions can facilitate digital inclusion, encourage multilingual education, and eradicate language barriers by allowing people to use technology in their own preferential language. But there are still a lot of issues, like standardized orthographies, a lack of digital sources, and regional differences in AI development. In addressing these challenges, it is paramount to adopt ethical AI frameworks that appreciate Africa’s diversity, local participation and sustained funding.
Keywords: Artificial intelligence (AI), Indigenous languages, Neural machine translation (NMT), Natural language processing (NLP), Digital inclusion
