Project Euphonia: advancing inclusive speech recognition through expanded data collection and evaluation - Martin, Alicia; MacDonald, Robert L.; Jiang, Pan-Pan; Ladewig, Marilyn; Cattiau, Julie; Heywood, Rus; Cave, Richard; Tobin, Jimmy; Nelson, Philip C.; Tomanek, Katrin (Frontiers in Language Sciences, 2025)
Speech recognition models, predominantly trained on standard speech, often exhibit lower accuracy for individuals with accents, dialects, or speech impairments. This disparity is particularly pronounced for economically or socially marginalized communities, including those with disabilities or diverse linguistic backgrounds. Project Euphonia, a Google initiative originally launched in English dedicated to improving Automatic Speech Recognition (ASR) of disordered speech, is expanding its data collection and evaluation efforts to include international languages like Spanish, Japanese, French and Hindi, in a continued effort to enhance inclusivity. This paper presents an overview of the extension of processes and methods used for English data collection to more languages and locales, progress on the collected data, and details about our model evaluation process, focusing on meaning preservation based on Generative AI.