A study of Assessment model of Oral English Imitation Reading in College Entrance Examination

被引：0
|
作者：
Li, Xin-Guang [1 ]
Long, Xiao-Lan [2 ]
Fan, Le-Xuan [2 ]
Liao, Yan-Min [2 ]
机构：
[1] Guangdong Univ Foreign Studies, Lab Language Engn & Comp, Guangzhou, Guangdong, Peoples R China
[2] Guangdong Univ Foreign Studies, Sch Informat Sci & Technol, Guangzhou, Guangdong, Peoples R China
来源：
2018 11TH INTERNATIONAL CONGRESS ON IMAGE AND SIGNAL PROCESSING, BIOMEDICAL ENGINEERING AND INFORMATICS (CISP-BMEI 2018) | 2018年
关键词：
Probabilistic Neural Network; Oral Paragraph Reading; Pronunciation Evaluation; Multi-parameter Evaluation Model;
D O I：
暂无
中图分类号：
R318 [生物医学工程];
学科分类号：
0831 ;
摘要：
In this paper, we propose a machine scoring method for imitation reading in Computer-based English Listening and Speaking Test (CELST). It focuses on how to evaluate the quality of paragraph reading. First of all, the paragraph is divided into sentences. After that, the individual sentences are scored from the dimensions of pronunciation accuracy, accent, rhythm, intonation and speech rate. Third, the score value of each sub-indicator is obtained by scoring the average value of the pronunciation accuracy of the plurality of sentences in the paragraph, the mean value of the accent score, the mean value of the rhythm score, the mean value of the intonation score and the mean value of the speech rate score. Finally, we determined the weight of each sub-indicator by consulting experts to obtain the assessment model. Experiment shows that our system scoring and teacher scoring are in good agreement. If the system is applied to help candidates to self-train reading imitation, it is expected to improve the candidates' ability to imitate the paragraph reading.
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页数：6
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