UW researchers investigated how state-of-the-art language models, including two from Google and one from OpenAI, evaluated human speech in job interviews, conference presentations and spoken English proficiency tests. The models scored responses from voices speaking English with five different accents: American, British, Chinese, Indian and Nigerian. The AI models generally ranked Chinese and Nigerian accents the lowest, Indian in the middle, and American and British the highest.





































