Automating Early Grade Reading Assessments (EGRA) in African Languages Using Voice-Recognition AI

Cally Ardington of the University of Cape Town in South Africa will develop an AI-powered voice-recognition model that performs Early Grade Reading Assessments (EGRA) in low- and middle-income countries (LMICs). Seventy percent of children in LMICs do not learn to read in any language, which severely affects their overall education and future prospects. Reading assessments, such as EGRA, test children on letter-sound knowledge, word reading, reading connected text, and answering questions on that text. They are critical for supporting reading programs but are currently expensive and time-consuming because they are administered one-on-one. They will perform a pilot study to determine whether a new open-source voice recognition program developed by Facebook (wav2vec), which is especially useful for languages with little training data, can automatically evaluate speech production and assess children's early reading abilities in African languages. They will validate EGRA-AI by adding it to an existing 120-school field trial using standard EGRA.