Formant-based english vowel assessment for Chinese in Taiwan

Jiang Chun Chen*, Wei Tang Hsu, J. S.Roger Jang, Ren Yuan Lyu, Yuang Chin Chiang

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

This paper proposes a formant-based approach for computer-assisted English vowel assessment. Various studies in formant-based speech synthesis have suggested the importance of formant coefficients; this motivates us to investigate pronunciation assessment using formant information instead of MFCC (Mel-frequency cepstral coefficients) alone. In particular, we explore the multistream HMM with the addition of formant information to improve the phoneme segmentation. We then propose the use of PCN (pronunciation confusion network) together with a formant-based confidence measure to improve error detection rates. Furthermore, the pros and cons of using cross-word phone model for both native speakers and L2 learners are discussed. Experimental results demonstrate the feasibility of the proposed approach for automatic vowel pronunciation assessment.

Original languageEnglish
Title of host publicationINTERSPEECH 2006 and 9th International Conference on Spoken Language Processing, INTERSPEECH 2006 - ICSLP
PublisherInternational Speech Communication Association
Pages1375-1378
Number of pages4
ISBN (Print)9781604234497
StatePublished - 2006
EventINTERSPEECH 2006 and 9th International Conference on Spoken Language Processing, INTERSPEECH 2006 - ICSLP - Pittsburgh, PA, United States
Duration: 17 09 200621 09 2006

Publication series

NameINTERSPEECH 2006 and 9th International Conference on Spoken Language Processing, INTERSPEECH 2006 - ICSLP
Volume3

Conference

ConferenceINTERSPEECH 2006 and 9th International Conference on Spoken Language Processing, INTERSPEECH 2006 - ICSLP
Country/TerritoryUnited States
CityPittsburgh, PA
Period17/09/0621/09/06

Keywords

  • Assessment
  • Computer assisted pronunciation training
  • Formant
  • Pronunciation confusion network
  • Speech recognition

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