Landmark of Mandarin nasal codas and its application in pronunciation error detection

Yanlu Xie, Mark Hasegawa-Johnson, Leyuan Qu, Jinsong Zhang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

L2 learners of Mandarin have difficulty learning native-like pronunciation of nasal codas. In order to help them learn native-like pronunciation, we propose to develop targeted classifiers for automatic pronunciation error detection. In this paper, perceptual experiments with modified speech are designed to analyze the exact position of the landmark of a nasal coda. Based on perceptual results from isolated words, we propose that information about nasal coda place of articulation is most dense near a landmark at the center of the nasalized vowel. Landmarks detected in a database of Japanese learners of Mandarin, and classified as correct vs. incorrect using an SVM. The result shows that the detection performance of the SVM+Landmark system is similar to that of a DNN-HMM+MFCC system. When the two systems are combined, an FRR of 4.6% is achieved at DA of 83.9%. This performance is comparable to that of previously developed classifiers for 16 common Mandarin pronunciation errors.

Original languageEnglish (US)
Title of host publication2016 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages5370-5374
Number of pages5
ISBN (Electronic)9781479999880
DOIs
StatePublished - May 18 2016
Event41st IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016 - Shanghai, China
Duration: Mar 20 2016Mar 25 2016

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume2016-May
ISSN (Print)1520-6149

Other

Other41st IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016
CountryChina
CityShanghai
Period3/20/163/25/16

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Keywords

  • Landmark
  • computer aided pronunciation training
  • nasal coda
  • pronunciation error detection

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

Cite this

Xie, Y., Hasegawa-Johnson, M., Qu, L., & Zhang, J. (2016). Landmark of Mandarin nasal codas and its application in pronunciation error detection. In 2016 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016 - Proceedings (pp. 5370-5374). [7472703] (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings; Vol. 2016-May). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICASSP.2016.7472703