Jwumasay joo-maJwumasay joo-maAnnotate, review and evaluate Yoruba language data for AI training and model evaluation.
Bilingual annotation is the work of deciding what text or speech actually means, then recording that decision in a form a model can learn from. For Yoruba that covers labelling intent and sentiment, checking whether a translation preserves meaning rather than words, transcribing speech accurately, and judging which of two model outputs a native speaker would actually accept.
Including tone marking, which most existing datasets get wrong or omit. Corpshore treats language varieties as distinct rather than flattening them, because a model trained on a flattened dataset fails precisely on the speakers who were flattened.
Corpshore runs annotation, evaluation and data collection for AI teams across 18+ countries in 35+ languages. Work is assigned by qualification and availability, not by location and every task shows its rate before you reserve it.