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REPORT ON THE 2006 INTERNATIONAL SYMPOSIUM OF COMPUTER ASSISTED LANGUAGE LEARNING: RESEARCH AND DEVELOPMENT OF CALL IN CHINA
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作者 梁毅军 《Chinese Journal of Applied Linguistics》 2006年第6期122-125,121,共5页
This paper reviews (CALL 2006) held on June 2-4, 2006 in Beijing, China. It also describes the research and development of CALL in China and reflects on the problems as a result of this symposium.
关键词 computer assisted language learning (CALL) research PROBLEMS EFL
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A new formant feature and its application in Mandarin vowel pronunciation quality assessment
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作者 卢小春 潘复平 +1 位作者 尹俊勋 胡维平 《Journal of Central South University》 SCIE EI CAS 2013年第12期3573-3581,共9页
In order to improve the Mandarin vowel pronunciation quality assessment, a nox/el formant feature was proposed and applied to formant classification for Chinese Mandarin vowel pronunciation quality evaluation. Formant... In order to improve the Mandarin vowel pronunciation quality assessment, a nox/el formant feature was proposed and applied to formant classification for Chinese Mandarin vowel pronunciation quality evaluation. Formant candidates of each frame were plotted on the time-frequency plane to form a bitmap, and its Gabor feature was extracted to represent the formant trajectory. The feature was then classified by using GMM model and the classification posterior probability was mapped to pronunciation quality grade. The experiments of comparing the Gabor transformation based formant trajectory feature with several other kinds of traditionally used features show that with this method, a human-machine scoring correlation coefficient (CC) of 0.842 can be achieved, which is better than the result of 0.832 by traditional speech recognition techniques. At the same time, considering that the long-term information of formant classification and the short-term information of speech recognition technique are complementary to each other, it is investigated to combine their results with linear or nonlinear methods to further improve the evaluation performance. As a result, experiments on PSK show that the best CC of 0.913, which is very close to the correlation of inter-human rating of 0.94, is gotten by using neural network. 展开更多
关键词 computer assisted language learning speech recognition Gaussian mixture model FORMANT Gabor feature NEURALNETWORK
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