Efficient pronunciation assessment of taiwanese-accented english based on unsupervised model adaptation and dynamic sentence selection

Chung-Hsien Wu, Hung Yu Su, Chao Hong Liu

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

This chapter presents an efficient approach to personalized pronunciation assessment of Taiwaneseaccented English. The main goal of this study is to detect frequently occurring mispronunciation patterns of Taiwanese-accented English instead of scoring English pronunciations directly. The proposed assessment help quickly discover personalized mispronunciations of a student, thus English teachers can spend more time on teaching or rectifying students' pronunciations. In this approach, an unsupervised model adaptation method is performed on the universal acoustic models to recognize the speech of a specific speaker with mispronunciations and Taiwanese accent. A dynamic sentence selection algorithm, considering the mutual information of the related mispronunciations, is proposed to choose a sentence containing the most undetected mispronunciations in order to quickly extract personalized mispronunciations. The experimental results show that the proposed unsupervised adaptation approach obtains an accuracy improvement of about 2.1% on the recognition of Taiwanese-accented English speech.

Original languageEnglish
Title of host publicationMultidisciplinary Computational Intelligence Techniques
Subtitle of host publicationApplications in Business, Engineering, and Medicine
PublisherIGI Global
Pages12-30
Number of pages19
ISBN (Print)9781466618305
DOIs
Publication statusPublished - 2012 Dec 1

Fingerprint

Students
Teaching
Acoustics

All Science Journal Classification (ASJC) codes

  • Computer Science(all)

Cite this

Wu, C-H., Su, H. Y., & Liu, C. H. (2012). Efficient pronunciation assessment of taiwanese-accented english based on unsupervised model adaptation and dynamic sentence selection. In Multidisciplinary Computational Intelligence Techniques: Applications in Business, Engineering, and Medicine (pp. 12-30). IGI Global. https://doi.org/10.4018/978-1-4666-1830-5.ch002
Wu, Chung-Hsien ; Su, Hung Yu ; Liu, Chao Hong. / Efficient pronunciation assessment of taiwanese-accented english based on unsupervised model adaptation and dynamic sentence selection. Multidisciplinary Computational Intelligence Techniques: Applications in Business, Engineering, and Medicine. IGI Global, 2012. pp. 12-30
@inbook{547c0e5d206243fc92c2a110f1f485b3,
title = "Efficient pronunciation assessment of taiwanese-accented english based on unsupervised model adaptation and dynamic sentence selection",
abstract = "This chapter presents an efficient approach to personalized pronunciation assessment of Taiwaneseaccented English. The main goal of this study is to detect frequently occurring mispronunciation patterns of Taiwanese-accented English instead of scoring English pronunciations directly. The proposed assessment help quickly discover personalized mispronunciations of a student, thus English teachers can spend more time on teaching or rectifying students' pronunciations. In this approach, an unsupervised model adaptation method is performed on the universal acoustic models to recognize the speech of a specific speaker with mispronunciations and Taiwanese accent. A dynamic sentence selection algorithm, considering the mutual information of the related mispronunciations, is proposed to choose a sentence containing the most undetected mispronunciations in order to quickly extract personalized mispronunciations. The experimental results show that the proposed unsupervised adaptation approach obtains an accuracy improvement of about 2.1{\%} on the recognition of Taiwanese-accented English speech.",
author = "Chung-Hsien Wu and Su, {Hung Yu} and Liu, {Chao Hong}",
year = "2012",
month = "12",
day = "1",
doi = "10.4018/978-1-4666-1830-5.ch002",
language = "English",
isbn = "9781466618305",
pages = "12--30",
booktitle = "Multidisciplinary Computational Intelligence Techniques",
publisher = "IGI Global",

}

Wu, C-H, Su, HY & Liu, CH 2012, Efficient pronunciation assessment of taiwanese-accented english based on unsupervised model adaptation and dynamic sentence selection. in Multidisciplinary Computational Intelligence Techniques: Applications in Business, Engineering, and Medicine. IGI Global, pp. 12-30. https://doi.org/10.4018/978-1-4666-1830-5.ch002

Efficient pronunciation assessment of taiwanese-accented english based on unsupervised model adaptation and dynamic sentence selection. / Wu, Chung-Hsien; Su, Hung Yu; Liu, Chao Hong.

Multidisciplinary Computational Intelligence Techniques: Applications in Business, Engineering, and Medicine. IGI Global, 2012. p. 12-30.

Research output: Chapter in Book/Report/Conference proceedingChapter

TY - CHAP

T1 - Efficient pronunciation assessment of taiwanese-accented english based on unsupervised model adaptation and dynamic sentence selection

AU - Wu, Chung-Hsien

AU - Su, Hung Yu

AU - Liu, Chao Hong

PY - 2012/12/1

Y1 - 2012/12/1

N2 - This chapter presents an efficient approach to personalized pronunciation assessment of Taiwaneseaccented English. The main goal of this study is to detect frequently occurring mispronunciation patterns of Taiwanese-accented English instead of scoring English pronunciations directly. The proposed assessment help quickly discover personalized mispronunciations of a student, thus English teachers can spend more time on teaching or rectifying students' pronunciations. In this approach, an unsupervised model adaptation method is performed on the universal acoustic models to recognize the speech of a specific speaker with mispronunciations and Taiwanese accent. A dynamic sentence selection algorithm, considering the mutual information of the related mispronunciations, is proposed to choose a sentence containing the most undetected mispronunciations in order to quickly extract personalized mispronunciations. The experimental results show that the proposed unsupervised adaptation approach obtains an accuracy improvement of about 2.1% on the recognition of Taiwanese-accented English speech.

AB - This chapter presents an efficient approach to personalized pronunciation assessment of Taiwaneseaccented English. The main goal of this study is to detect frequently occurring mispronunciation patterns of Taiwanese-accented English instead of scoring English pronunciations directly. The proposed assessment help quickly discover personalized mispronunciations of a student, thus English teachers can spend more time on teaching or rectifying students' pronunciations. In this approach, an unsupervised model adaptation method is performed on the universal acoustic models to recognize the speech of a specific speaker with mispronunciations and Taiwanese accent. A dynamic sentence selection algorithm, considering the mutual information of the related mispronunciations, is proposed to choose a sentence containing the most undetected mispronunciations in order to quickly extract personalized mispronunciations. The experimental results show that the proposed unsupervised adaptation approach obtains an accuracy improvement of about 2.1% on the recognition of Taiwanese-accented English speech.

UR - http://www.scopus.com/inward/record.url?scp=84898207051&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84898207051&partnerID=8YFLogxK

U2 - 10.4018/978-1-4666-1830-5.ch002

DO - 10.4018/978-1-4666-1830-5.ch002

M3 - Chapter

AN - SCOPUS:84898207051

SN - 9781466618305

SP - 12

EP - 30

BT - Multidisciplinary Computational Intelligence Techniques

PB - IGI Global

ER -

Wu C-H, Su HY, Liu CH. Efficient pronunciation assessment of taiwanese-accented english based on unsupervised model adaptation and dynamic sentence selection. In Multidisciplinary Computational Intelligence Techniques: Applications in Business, Engineering, and Medicine. IGI Global. 2012. p. 12-30 https://doi.org/10.4018/978-1-4666-1830-5.ch002