Fagoroye Ayomide Emmanuel is an AI researcher and software engineer with a focus on low-resource languages and ethical AI practices. His field of expertise spans machine learning, natural language processing, and speech technology. His contributions have been extensive toward the advancement of AI for African languages, especially Yoruba. His work emphasizes the importance of cultural sensitivity, speaker diversity, and ethical data collection in developing language models. Of late, Ayomide has developed standards and best practices that go into the collection and processing of speech datasets in African languages, ensuring ethical, linguistic, and technical best practices. His research has tackled complex challenges in low-resource language processing, including data scarcity, model fairness, and ethical considerations in acoustic data collection. With experience in both industry and academia, Ayomide has collaborated with international organizations and research groups, contributing to projects aimed at preserving linguistic diversity and improving AI accessibility.
He sees himself as a dynamic technologist and is eager to apply his expertise to close the gap between advanced AI and underserved languages so that AI will be beneficial for speakers of all languages, regardless of their demographic or linguistic background.