Lanfrica Talks #10 | Modeling language from raw speech in an unsupervised manner by Gašper Beguš

Gašper Beguš an Assistant Professor at the Department of Linguistics at UC Berkeley where he directs the Berkeley Speech and Computation Lab. 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. His research focuses on developing deep-learning models for speech data. More specifically, he trains models to learn representations of spoken words from raw audio inputs. 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.

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