Dr. Sarah Luger, Technology Group Principal at Orange Silicon Valley, has launched our Bambara-French Machine Translation Competition. We invite our interested readers to participate and share with others this compelling opportunity to increase language representation in telco technologies.
The competition focuses on the development of a machine translation model for Bambara, a low-resource language. It is predominantly spoken in Mali and is one of the country’s 13 national languages, with 15 million speakers. Bambara is one of the closely related Manding languages, which are part of the larger Mandé language family.
Recent advancements in Neural Machine Translation have made designing high-resource language translation models achievable — for big tech companies with access to large sets of parallel, translated data. However, low-resource languages like Bambara — ones that do not have extensive digital data sets and online communities, often because they are primarily spoken and not written — have benefited much less. Additionally, linguistic research is often lacking in low-resource languages, making conventional natural language processing (NLP) tasks more difficult.
After they have been approved and been given access to a common data set, competitors will create Bambara-to-French and French-to-Bambara translation models. Our Competition page includes additional information about evaluation criteria, prizes, workshop opportunities, and more. The competition begins on August 1st. Dr. Luger’s professional background blends NLP engineering and product architecture, responsible AI, conversational AI, and emerging machine translation technologies for under-resourced languages. She built several “first-of-a-kind” NLP solutions — including automated email and text response experiences that are mainstream today — and received both a Master of Science and PhD in Informatics from University of Edinburgh in Edinburgh, Scotland.