Project Atlas
A large scale annotation effort designed to improve AI understanding of real world English speech by classifying native versus non-native speakers and identifying regional accents. The project involved transcript verification, pronunciation and intelligibility tagging, and selection of highest quality model outputs across thousands of audio samples and iterative training cycles. Consistency was maintained through detailed guidelines, calibration reviews, inter-annotator agreement checks and periodic quality audits.