This award was provided as part of NSF's Social, Behavioral and Economic Sciences (SBE) Postdoctoral Research Fellowships (SPRF) program and SBE's Linguistics program. The goal of the SPRF program is to prepare promising, early career doctoral-level scientists for scientific careers in academia, industry or private sector, and government. SPRF awards involve two years of training under the sponsorship of established scientists and encourage Postdoctoral Fellows to perform independent research. NSF seeks to promote the participation of scientists from all segments of the scientific community, including those from underrepresented groups, in its research programs and activities; the postdoctoral period is considered to be an important level of professional development in attaining this goal. Each Postdoctoral Fellow must address important scientific questions that advance their respective disciplinary fields. Under the sponsorship of Dr. Janet van Hell, Dr. Carrie Jackson, and Dr. Matthew Carlson at Penn State University, this postdoctoral fellowship award supports an early career scientist investigating how people adapt to foreign-accented pronunciation. Adaptation is the process by which listeners adjust to unfamiliar spoken sounds produced by an accented speaker. Existing research has shown that adaptation to accented speech often happens quickly and automatically. This project will extend such research to Mandarin Chinese. Mandarin is a lexical tone language that can use pitch patterns to differentiate syllables and words. Adult second language learners of Mandarin typically struggle to control and remember tones, leading them to make frequent tone errors. For listeners, these errors might affect adaptation to other aspects of foreign-accented Mandarin, either slowing their accommodation of accented pronunciation, or causing them to ignore all tones. This research may help us to understand why adaptation to accented speech sometimes fails to occur. By focusing on ways that second language pronunciation impacts listeners, this research also has the potential to inform language teachers and program administrators on how best to prioritize pronunciation in language training.

This research addresses the occurrence of unsystematic tone errors within a foreign-accented speaker's Mandarin speech. Unsystematic tone errors are unpredictable for listeners in terms of both when and how they will occur. The focus on unsystematic pronunciation errors adds a critical dimension that must be accounted for in models of listener adaptation. Specifically, this project examines word recognition in native Mandarin listeners, by contrasting listener responses when a foreign-accented speaker produces frequent unsystematic tone errors compared to when a speaker produces few tone errors. Using a forced-choice word recognition paradigm, and measuring eye-movements during word recognition, two sets of experiments will test whether Mandarin listeners can ignore (i.e., down-weight) tones, and whether this down-weighting impacts the speed and outcome of word recognition. A further set of experiments will examine how previous experience teaching foreign language impacts listeners? adaptive processes. Together, these experiments will shed light on accent adaption in tonal languages, and provide new insight into the importance of tonal accuracy in second language Mandarin speech. By involving language teachers directly in the research, the project has the potential to build bridges between laboratory science and classroom settings, which will lead to better informed language instructors, and may provide future opportunities to move scientific investigations into classrooms.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

Agency
National Science Foundation (NSF)
Institute
SBE Office of Multidisciplinary Activities (SMA)
Application #
2004279
Program Officer
Josie S. Welkom
Project Start
Project End
Budget Start
2020-08-15
Budget End
2022-07-31
Support Year
Fiscal Year
2020
Total Cost
$143,000
Indirect Cost
Name
Pelzl Eric
Department
Type
DUNS #
City
State College
State
PA
Country
United States
Zip Code
16801