TweetyBERT parses canary songs to better understand how brains learn language

A new machine learning model, TweetyBERT, automatically segments and classifies canary vocalizations with expert-level accuracy, offering a scalable platform for neuroscience, providing insights into the neural basis of how the brain learns and produces language, and offering potential applications for understanding animal vocalization more broadly. The study by University of Oregon researchers appears in the journal Patterns.