Postdoctoral Research Fellow
- Research Associate funded by the Leverhulme Trust
I am a Postdoctoral Research Fellow working with Prof. Kate Nation. I use corpus data to inform our understanding on how children learn to read. We are interested in knowing the statistical properties of children's written language experience, and their own writing production. We then relate these statistics to how they learn to read, using a variety of behavioural methods.
I completed my Ph.D. at University of Wisconsin-Madison, studying the processes of language production and comprehension, and the connections between the two. I used a combination of behavioral methods, corpus analysis and computational modeling to examine the role of language experience on human sentence processing.
My broad research interests include first and second language learning and processing, neural network modeling, corpus analyses, cross-linguistic comparisons.
Production predicts comprehension: Animacy effects in Mandarin relative clause processing
Hsiao Y. and MacDonald MC., (2016), Journal of Memory and Language, 89, 87 - 109
Agent-patient similarity affects sentence structure in language production: evidence from subject omissions in Mandarin
Hsiao Y. et al, (2014), Frontiers in Psychology, 5
Experience and generalization in a connectionist model of Mandarin Chinese relative clause processing
Hsiao Y. and MacDonald MC., (2013), Frontiers in Psychology, 4
Dissociation between visual attention and visual mental imagery
Thompson WL. et al, (2011), Journal of Cognitive Psychology, 23, 256 - 263
Learning that classifiers count: Mandarin-speaking children’s acquisition of sortal and mensural classifiers
Li P. et al, (2010), Journal of East Asian Linguistics, 19, 207 - 230