Tzu-Yun Tung / t͡sɨ̌ ýn tǔŋ/ is a postdoctoral scholar supervised by Professor Alan Yu. She was trained as a computational neurolinguist, using both computational modeling and electrophysiological measurement to understand language processing and speech perception in real time. Her goal is to develop a research program that is theoretically motivated, experimentally rigorous, and socially relevant from a developmental or clinical perspective.
Tzu-Yun has studied how neural encodings of phonetic cues (e.g., tonal differences) affect speech perception, as well as how memory retrieval and prediction guide online sentence parsing. She leverages both large language models (LLMs) and computational cognitive models (e.g., ACT-R) to simulate human behaviors in response to naturalistic linguistic stimuli.
Tzu-Yun is broadly interested in the biological underpinnings of our linguistic knowledge, and how we integrate different levels (e.g., phonetic, morphemic, syntactic, semantic) of this knowledge to ensure successful speech recognition and language comprehension. Pushing forward, she is also looking forward to the opportunities to extend the research to developmental or clinical populations.
