Can a phonetically blind machine learn sublexical groups in Korean like us?
2025, 32nd Japanese/Korean Linguistics Conference, Cornell University
Phonology · Computational Linguistics · Korean Linguistics
Hi! I am Stanley Nam (he/him).
I recently completed my PhD in linguistics at the University of British Columbia, co-supervised by Gunnar Ólafur Hansson and Kathleen Currie Hall.
My research focuses on phonology, particularly on how speakers and machine-learning models perform on phonological tasks and what their behaviour can reveal about phonological theory.
My dissertation investigates how speakers and Transformer models apply selective processes. The focus is on whether their behaviour can be explained through transparent information, such as phonotactics, rather than latent information, such as etymology.
My MA thesis compared phonological neighbourhood networks in English and Korean, examining how global network structure differs across the two languages while showing comparable organizing principles.
I have also worked on finiteness in syntax and loanword adaptation.
I am currently based in Vancouver, Canada.
Nam, S. (2026). Can a Transformer Model Learn Sublexical Groups in Korean Like Us? Japanese/Korean Linguistics 32.
Nam, S. (2025). Korean honorific agreement as the marginal requirement for syntactic finiteness. Glossa 10(1).
Nam, S. (2021). The adaptation of English word-initial voiced stops in Korean: A diachronic approach. Studies in Phonetics, Phonology and Morphology 27(1), 3–25.
Kim, S.-H. and S. Nam. (2019). Revisiting vowel harmony in Korean sound-symbolic words: A corpus-based quantitative approach. The Journal of Studies in Language 35(3), 309–325.
2026, ICKL 2026, University of Sheffield
2025, 32nd Japanese/Korean Linguistics Conference, Cornell University
2025, 31st Manchester Phonology Meeting, University of Manchester