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General Information
    • ISSN: 2010-3689
    • Frequency: Bimonthly (2011-2014); Monthly (Since 2015)
    • DOI: 10.18178/IJIET
    • Editor-in-Chief: Prof. Dr. Steve Thatcher
    • Executive Editor: Ms. Nancy Y. Liu
    • Abstracting/ Indexing: EI (INSPEC, IET), Electronic Journals Library, Google Scholar, Crossref and ProQuest
    • E-mail: ijiet@ejournal.net
Prof. Dr. Steve Thatcher
QUniversity, Australia
It is my honor to be the editor-in-chief of IJIET. The journal publishes good-quality papers which focous on the advanced researches in the field of information and education technology. Hopefully, IJIET will become a recognized journal among the scholars in the related fields.

IJIET 2014 Vol.4(2): 167-171 ISSN: 2010-3689
DOI: 10.7763/IJIET.2014.V4.391

Automatic Judgment System for Chinese Retroflex and Dental Affricates Pronounced by Japanese Students

Akemi Hoshino and Akio Yasuda
Abstract—Chinese retroflex aspirates are generally difficult for Japanese students learning Chinese pronunciation. In particular, discriminating between utterances of aspirated dental and retroflex affricates is the most difficult for Japanese-speakers to learn. For the students' self-learning, the automatic judgment system was developed using a computer, so as to check the pronunciations by themselves. We extracted the features of correctly pronounced aspirated dental affricates ca[ʦ‘a], ci[ʦ‘i], ce[ʦ‘ɤ], and cu[ʦ‘u] and aspirated retroflex affricates cha[tʂ‘a], chi[tʂ‘i], che[tʂ‘ɤ], and chu[tʂ‘u] by observing the spectrum evolution of breathing power during both voice onset time and voiced period of sounds uttered by 40 Chinese native speakers. We developed a 35-channel computerized filter bank to analyze the evolution of the breathing power spectrum by using MATLAB and then automatically evaluated the utterances of the 50 Japanese students. At the same time, we asked to native Chinese speakers to evaluate the same students’ utterances for the reference. Our system rejected several samples that passed the screening by the native speakers. The success rates of the system were higher than 91% and 95% for aspirated retroflex and dental affricates, respectively.

Index Terms—Automatic pronunciation discrimination, Chinese aspirated retroflex and dental affricates, e-learning.

Akemi Hoshino is with Toyama National College of Technology, 1-2 Ebie, Neriya, ImizuCity, Toyama, 933-0293 Japan (e-mail: hoshino@ nc-toyama.ac.jp).
Akio Yasuda is with Tokyo University of Marine Science and Technology, 2-1-3 Etchujima, Koto-ku, Tokyo, 135-8533 Japan (e-mail: yasuda@kaiyodai.ac.jp).


Cite: Akemi Hoshino and Akio Yasuda, "Automatic Judgment System for Chinese Retroflex and Dental Affricates Pronounced by Japanese Students," International Journal of Information and Education Technology vol. 4, no. 2, pp. 167-171, 2014.

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