Research
I am a computational psycholinguist and experimental linguist, with research interests centered on sentence processing and the prosody-syntax interface.
My current research interests focus on how prosodic cues and information structure can help us disambiguate syntactic structures. I investigate how they influence the acceptability and processing of ambiguous/complex syntactic constructions. My research interests are all woven together by a central aim: understanding how people process ambiguous and complex syntactic structures across written and spoken modalities.
Currently, I am working on and am interested in:
- MA thesis project: Korean ditransitive structures (Publication: Shim & Han - Acceptability of Double Object Constructions in Korean Ditransitive Structures)
- Information Structure (focus)
- Punctuations
- Resumptive Pronouns in English
- Long distance anaphors in Korean
My broader aim is to better understand how AI models, including LLMs and TTS models, diverge from or converge with human performance in processing ambiguous linguistic inputs, and how humans in turn perceive AI-generated language compared to naturally produced utterances. By applying linguistic insights, I seek to deepen our understanding of both human language processing and the limitations of current language technologies.
Relevant work: I examine how modern AI, particularly Text-to-speech (TTS) models, often fail to produce reliable prosodic cues. I study how naïve human listeners perceive such synthetic speech: what they find acceptable or unnatural, and where and why those perceptions shift. To address these issues, I also work on developing pipelines and datasets aimed at improving prosody in TTS systems.