Gasper Begus

I am an Assistant Professor at the Department of Linguistics at UC Berkeley. Previously, I was an Assistant Professor at the University of Washington. Before that, I graduated with a Ph.D. from Harvard.

My research focuses on developing deep learning models for speech data. More specifically, I train models to learn representations of spoken words from raw audio outputs. I combine machine learning with behavioral experiments and statistical models to better understand how neural networks learn internal representations in speech and how humans learn to speak. I have 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), I propose 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.

I direct the Berkeley Speech and Computation Lab. Feel free to contact me if you’re interested in getting involved with the lab.

Department of Linguistics

UC Berkeley

1203 Dwinelle Hall #2650

Berkeley, CA 94720-2650


Oct 26, 2020 How to combine human behavioral experiments and CNNs? A new preprint is on arXiv.
Sep 23, 2020 Can deep convolutional network learn identity-based patterns? A new preprint is on arXiv.
Sep 15, 2020 I'll give a talk at MIT BCS Comp Lang
Jul 25, 2020 A deep neural network learns to produce new words
Jul 22, 2020 A new paper on lexical learning in GANs & latent space interpretability is out on arXiv.
Jul 8, 2020 A new paper is out in Frontiers in Artificial Intelligence.
Jul 1, 2020 I started a new job at UC Berkeley.