Comparing the effects of letter-based and syllable-based speaking rates on the pronunciation assessment of Korean speakers of English*
Author:
Funder
Korea National University of Education
Publisher
The Korean Society of Speech Sciences
Link
http://www.eksss.org/download/download_pdf?doi=10.13064/KSSS.2023.15.4.001
Reference23 articles.
1. Bates, D., Mächler, M., Bolker, B., & Walker, S. (2015). Fitting linear mixed-effects models using lme4. Journal of Statistical Software, 67(1), 1-48. 10.18637/jss.v067.i01
2. Chakrabarti, A., & Ghosh, J. K. (2011). AIC, BIC and recent advances in model selection. In P. S. Bandyopadhyay, & M. R. Forster (Eds.), Philosophy of statistics: Handbook of the philosophy of science (pp. 583-605). North Holland: Elsevier. 10.1016/B978-0-444-51862-0.50018-6
3. Chen, L., Zechner, K., Yoon, S. Y., Evanini, K., Wang, X., Louskina, A., Tao, J., ... Gyawali, B. (2018). Automated scoring of nonnative speech using the SpeechRaterSM v. 5.0 engine. ETS Research Report Series, 2018(1), 1-31. 10.1002/ets2.12198
4. Choi, N., & Jang, T. Y. (2023). Evaluation of English speaking proficiency under fixed speech rate: Focusing on utterances produced by Korean child learners of English. Phonetics and Speech Sciences, 15(1), 47-54. 10.13064/KSSS.2023.15.1.047
5. Chung, H. (2022). Relationships between rhythm and fluency indices and listeners’ ratings of Korean speakers’ English paragraph reading. Phonetics and Speech Sciences, 14(4), 25-33. 10.13064/KSSS.2022.14.4.025
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