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Project Descriptions
Spring 2025

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Interpretable generative AI, language in humans, animals, and machines

Gasper Begus, Professor  
Linguistics  

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This project looks at language in deep neural networks, animals (whales, elephants, spiders), and humans. We model spoken language from raw audio using deep generative neural networks (GANs). We use audio, neural, and behavioral data in spoken language to better understand and interpret deep learning models.

Role: The undergraduate student will help with:
(i) coding the models in Pytorch
(ii) audio signal processing
(iii) helping with data analysis (acoustic and statistical analysis in Praat, Librosa, R), interpreting the results

Qualifications: Coding knowledge in PyTorch (or Tensorflow) required, knowledge of machine learning theory. Students with interest in CS, cognitive science, linguistics, marine biology, and signal processing are very welcome to apply.

Hours: to be negotiated

Related website: https://www.gasperbegus.com
Related website: https://docs.google.com/document/d/1xrRXGssVcetcKnZ0wOORXgKE8WGaxahq3xDNF9juF0o/edit?usp=sharing

 Digital Humanities and Data Science   Social Sciences   Engineering, Design & Technologies

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