I am interested in how people perceive and learn about the world. Within this frame, I have been studying speech as a particular medium, and examining how people learn, use, and represent speech in their brain. Currently, I am a PhD student at the University of Maryland, with affiliations in NACS (Neuroscience and Cognitive Science), the Department of Linguistics, and the Department of Computer Science/UMIACS (which I am working on a Master’s Degree in).
I am also a pianist who plays what I love like a broken record. Other than performing, I also enjoy studying theories of music and music history, occasionally composing in the old style. I take music not as a career but very seriously, because as Seneca says:
Mihi crede, verum gaudium res severa est. (Sen. Ep. 23.4)
Chronologically, I am from Kunming, a city in Southwest China. Intriguingly, the main dialect of Kunming is a Northern dialect, with close relation to standard Mandarin. Here is a little project on my hometown dialect. I graduated from the University of Rochester in 2020, with a degree in Brain & Cognitive Sciences (B.S.) and another in Linguistics (B.A.).
Rhythm in Speech
How does the brain represent and learn rhythm in speech? Is this related to musical rhythm?
Input to Phonetic Learning Models
Number and composition of speakers affect the outcome of a model of early phonetic learning.
Foreign-Accented Speech Corpus
A corpus containing native and Mandarin-accented English, including isolated words and connected speech.
(Click on project for related publications.)
Broadly, I am interested in human perception and cognition. Among all the things humans perceive and think about, I have mostly been focusing on speech. Speech is something we perceive and use effortlessly but is unique to humans. It is also something that machine learning tries hard to match human performance on. How do we do this? In my PhD, I focus on speech rhythm — temporal regularities of sounds — and examine how speech rhythm is represented by the human brain. I use a interdisciplinary approach, from phonology and music psychology to machine learning and time series analysis, to study how speech rhythm is represented in the brain and learned as we acquire our native language.
Evolution of Musical Cadences
Semester project simulating the change of cadences in music, from the 1400s to the Renaissance.
Confirmation Bias and Information Structure
Replication and expansion on an existing model of confirmation bias, with human data.