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.
A team led by University of Washington researchers found that large language models, such as ChatGPT, can make social media bots more sophisticated at evading detection. But these models can also improve systems that detect bots.
Two faculty members at the University of Washington have been awarded early-career fellowships from the Alfred P. Sloan Foundation. The new Sloan Fellows, announced Feb. 15, are Brianna Abrahms, an assistant professor in the Department of Biology, and Yulia Tsvetkov, an assistant professor in the Paul G. Allen School of Computer Science & Engineering.