BIASED PHONOLOGICAL LEARNING: CROSS-LINGUISTIC COMPARISON
This project investigates the role of learning biases in acquiring sound patterns of languages among children from 4 to 7 years of age, who learn Cantonese, English, and Korean as their first language. Various work on language acquisition show cases where the outcome of language learning does not perfectly reflect what was in the input: learners may fail to acquire some input patterns or they may make some assumptions when input is ambiguous. When a discrepancy between the input and the learning outcome is observed, a conclusion has been made that the learning was biased in a certain way. This project explores types of learning biases children bring to the task of learning sound patterns. We also investigate the causal relationship of learning biases to phenomena of natural language acquisition and to the shapes of different languages.
Team: Youngah, Yoonsang, Arthur
In this project, we explore how people interpret imitative quotatives “and then he was like…” in several conditions.
Team: Youngah, Arthur
HIERARCHICAL STRUCTURE OF MULTIMORPHEMIC WORDS: EVIDENCE FROM AN OVERT PRIMING EXPERIMENT
This project explores a psycholinguistic reality of the hierarchical structure of words with multiple morphemes. In generative morphology, it has been assumed that individual morphemes in a complex derived word are represented in a hierarchical fashion with binary branching. We investigate its reality in L1 as well as L2 speakers’ mind.
Team: Youngah, Yoonsang, Arthur, Eileen
COMPUTATIONAL MODELING OF LEARNING PHONOTACTICS
The goal of this project is to develop a computational software tool designed to simulate phonotactic patterns of languages with metric information.
Team: Youngah, Ryan
Structural priming in Cantonese
We are running a follow-up study of Song & Do (2016) ‘Cross-linguistic syntactic priming in bilinguals: priming of the subject-to-object raising construction between English and Korean.’ Bilingualism: Language and Cognition. [link]
Team: Youngah, Yoonsang, Ryan