2090A Foreign Language Building
707 South Mathews
Urbana, Illinois 61801
Phonetics, Phonology, Tone, Intonation, Tone sandhi, Prosody modeling, Second Language Fluency, Pronunciation training, Chinese proficiency testing
Dr. Chilin Shih is a Chinese linguist in phonology, phonetics and speech. Her work is interdisciplinary in nature: It is situated in the intersection of linguistics, speech technologies and language teaching. She has worked for ten years on multilingual text-to-speech systems at Bell Laboratories before joining UIUC, and has continued the linguistic work analyzing multilingual prosodic systems and building models to predict prosody from text, including intonation models and duration models. She has applied speech technologies in language teaching and has built a tone training and testing system Prosody Tutor under an NSF grant. The Prosody Tutor uses an adaptive approach to prosody tutoring and adjusts teaching materials automatically according to students' previous responses. Dr. Shih had another NSF grant working on second language fluency evaluation. The project is based on data collected from the creative output paradigm that she implemented in the third year and fourth year Chinese language classes at UIUC, where the curriculum centers around public speaking training exercises such as debates, interviews, and speeches.
Ph.D. in Linguistics. University of California--San Diego (1986)
An Interdisciplinary Study of the Dynamics of Second Language Fluency, NSF, 2007-2010
Translating Prosody in an English/Chinese Language Tutoring System, NSF, 2006-2009
Multi-media Interlanguage speech corpus for intelligent Chinese pronunciation training, Innovation Center for Language Resources, China. 2017-2020
The Improvement of Elicited Imitation for Chinese Proficiency Testing, 2017
Additional Campus Affiliations
Professor, East Asian Languages and Cultures
Head, East Asian Languages and Cultures
Honors & Awards
Helen Corely Petit Scholar
Campus Award for Innovation in Undergraduate Instruction Using Educational Technologies
Arnold O. Beckman Research Award
Gent, H., Adams, C., Shih, C., & Tang, Y. (2022). Deep Learning for Prosody-Based Irony Classification in Spontaneous Speech. Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH, 2022-September.
Le, G., Shih, C., & Tang, Y. (2022). A Laryngographic Study on the Voice Quality of Northern Vietnamese Tones under the Lombard Effect. Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH, 2022-September.
Sun, Y., & Shih, C. (2021). Boundary-conditioned anticipatory tonal coarticulation in Standard Mandarin. Journal of Phonetics, 84, . https://doi.org/10.1016/j.wocn.2020.101018
Yan, X., Lei, Y., & Shih, C. (2020). A corpus-driven, curriculum-based Chinese elicited imitation test in US universities. Foreign Language Annals, 53(4), 704-732. https://doi.org/10.1111/flan.12492
Gao, Y. A., Toscano, J. C., Shih, C., & Tanner, D. (2019). Reassessing the electrophysiological evidence for categorical perception of Mandarin lexical tone: ERP evidence from native and naïve non-native Mandarin listeners. Attention, Perception, and Psychophysics, 81(2), 543-557. https://doi.org/10.3758/s13414-018-1614-8