Research Expertise and Interest

computational linguistics, machine learning, artificial intelligence, Generative AI, Deep Learning, speech processing, NLP, phonology, articulatory and acoustic phonetics, historical linguistics, Indo-European linguistics

Research Description

Gašper Beguš is an Associate Professor at the Department of Linguistics at UC Berkeley.  Before coming to Berkeley, he was an Assistant Professor at the University of Washington and before that he graduated with a Ph.D. from Harvard. He combines machine learning and statistical modeling with neuroimaging and behavioral experiments to better understand how neural networks learn internal representations in speech and how humans learn to speak. He has worked and published on sound systems of various language families such as Indo-European, Caucasian, and Austronesian languages.

In a recent set of papers (here and here), he proposes that language acquisition can be modeled with Generative Adversarial Networks and propose a technique for exploring the relationship between learned representations and latent space in deep convolutional networks.

Dr. Beguš directs the Berkeley Speech and Computation Lab. Dr. Beguš also serves as the College Principal of the oldest residential college in the country, the Bowles Hall Residential College.