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Volume 29 Issue 5
September  2014
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Jia Jia, Wai-Kim Leung, Yu-Hao Wu, Xiu-Long Zhang, Hao Wang, Lian-Hong Cai, Helen M. Meng. Grading the Severity of Mispronunciations in CAPT Based on Statistical Analysis and Computational Speech Perception[J]. Journal of Computer Science and Technology, 2014, 29(5): 751-761. DOI: 10.1007/s11390-014-1465-2
Citation: Jia Jia, Wai-Kim Leung, Yu-Hao Wu, Xiu-Long Zhang, Hao Wang, Lian-Hong Cai, Helen M. Meng. Grading the Severity of Mispronunciations in CAPT Based on Statistical Analysis and Computational Speech Perception[J]. Journal of Computer Science and Technology, 2014, 29(5): 751-761. DOI: 10.1007/s11390-014-1465-2
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Grading the Severity of Mispronunciations in CAPT Based on Statistical Analysis and Computational Speech Perception

  • 1. Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China;
    2. Tsinghua National Laboratory for Information Science and Technology, Tsinghua University, Beijing 100084, China;
    3. Key Laboratory of Pervasive Computing, Ministry of Education, Beijing 100084, China;
    4. Human-Computer Communications Laboratory, Department of Systems Engineering and Engineering Management The Chinese University of Hong Kong, Shatin, Hong Kong, China;
    5. Tsinghua-CUHK Joint Research Center for Media Sciences, Technologies and Systems, Shenzhen 518055, China

Funds: This work is supported by the National Basic Research 973 Program of China under Grant No. 2013CB329304, the National Natural Science Foundation of China under Grant No. 61370023, and the Major Project of the National Social Science Foundation of China under Grant No. 13&ZD189. This work is also partially supported by the General Research Fund of the Hong Kong SAR Government under Project No. 415511 and the CUHK Teaching Development Grant.
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  • Author Bio:

    Jia Jia is an associate professor in the Department of Computer Science and Technology, Tsinghua University, Beijing. She got her B.S. and Ph.D. degrees both in computer science and technology from Tsinghua University in 2003 and 2008 respectively. Her main research interest is human computer speech interaction and social a?ective computing.

  • Received Date: March 15, 2014
  • Revised Date: July 13, 2014
  • Published Date: September 04, 2014
    Abstract
  • Computer-aided pronunciation training (CAPT) technologies enable the use of automatic speech recognition to detect mispronunciations in second language (L2) learners' speech. In order to further facilitate learning, we aim to develop a principle-based method for generating a gradation of the severity of mispronunciations. This paper presents an approach towards gradation that is motivated by auditory perception. We have developed a computational method for generating a perceptual distance (PD) between two spoken phonemes. This is used to compute the auditory confusion of native language(L1). PD is found to correlate well with the mispronunciations detected in CAPT system for Chinese learners of English, i.e., L1 being Chinese (Mandarin and Cantonese) and L2 being US English. The results show that auditory confusion is indicative of pronunciation confusions in L2 learning. PD can also be used to help us grade the severity of errors (i.e., mispronunciations that confuse more distant phonemes are more severe) and accordingly prioritize the order of corrective feedback generated for the learners.
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    • References (12)
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