A Low-Resource Language Translation: French To Mooré
Résumé
Natural Language Processing (NLP) is an exciting field of artificial intelligence with the goal of enabling machines to understand human language in a natural way. Neural Machine Translation (NMT) stands out as one of the most promising applications of NLP, offering the ability to effectively translate text from a source language to a target language. In recent years, NMT has experienced significant advances, marking a major milestone in the development of automatic translation systems. Through the use of neural networks, NMT has demonstrated an ability to capture the nuances of language, thereby improving the quality of translations and making the experience of multilingual communication more seamless and precise. This evolution has opened new perspectives in areas such as international collaboration, intercultural understanding, and the global dissemination of information. However, most African languages, especially those in Burkina Faso, have received very little research attention in this context. In this article, we propose automated translation models French to Mooré based on Transformers. We achieved a BLEU score of 71.18 for the automated for the second model, French to Mooré translation.
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