BIASED PHONOLOGICAL LEARNING: the role of production in learning unnatural phonology 

This project investigates the role of production in learning unnatural sound patterns. Evidence for the naturalness bias is weak and we believe that this might be due to the methodological settings of most studies. The majority of artificial learning studies employ perception-only methods and not production. We plan to investigate the role of production by comparing learning in both settings: perception-only and perception and production. 

Team: Youngah, Marcelo


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

The role of visual cues in learning ideophones

Ideophones are marked words that depict sensory imagery and occur in many languages. It has been found that these words are easier to learn which might be due to their depictive properties. In this project we investigate whether visual cues such as lip rounding and mouth opening help in learning ideophones. 

Team: Youngah, Arthur


Chinese Ideophone Database (CHIDEOD) is an open-source dataset coded in a user-friendly format, which collects 3453 unique onomatopoeia and ideophones (mimetics) of Mandarin Chinese, as well as Middle Chinese and Old Chinese (based on Baxter & Sagart 2014). These are analyzed according to a wide range of linguistic features, including phonological, semantic, as well as orthographic ones. CHIDEOD was created on the basis of data collection and analysis conducted by Arthur Thompson in our lab in collaboration with Thomas Van Hoey in National Taiwan University. For individual sources and files relevant to the database, please visit here:

Team: Arthur, Thomas van Huey


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

Artificial learning of Tone Sandhi

Chinese tone sandhis can be broadly classified as left-dominant or right-dominant according to the position of the syllable preserving the citation tone. Right-dominant Chinese sandhis are more common than left-dominant sandhis, which might be attributed to phonetic naturalness such as duration. In studies of phonetic naturalness bias and structural simplicity bias, researchers normally control one factor to investigate another factor. When a certain effect is found, it could be the combinatorial effect. In this project we investigate the role of phonetic naturalness vs. structural simplicity in learning tone sandhi. 

Team: Youngah, Tingyu


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