Abstract
This paper discusses pronunciation quality scoring for single syllable word in Putonghua Shuiping Ceshi (PSC) that is a nationwide spoken test to evaluate the standard level and the practical ability that an individual uses the mandarin in china. This study mainly includes some algorithms about the syllable separation, acoustic units selection, posterior probability scoring, threshold values setting and neural network combination. Experiment shows that the proposed approach achieves a high correlation of 0.731, a value very close to 0.786 between human experts. It is also observed that the combination method of neural network gets the best evaluation result. This method is eligible for the automatic scoring in PSC.
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© 2012 Springer-Verlag GmbH Berlin Heidelberg
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Zhang, L., Li, H., Wang, J. (2012). Pronunciation Quality Scoring for Single Syllable Word in PSC. In: Luo, J. (eds) Affective Computing and Intelligent Interaction. Advances in Intelligent and Soft Computing, vol 137. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-27866-2_38
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DOI: https://doi.org/10.1007/978-3-642-27866-2_38
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-27865-5
Online ISBN: 978-3-642-27866-2
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