基于人工神经网络的韩国汉语学习者口语流利性评价研究  

On the Evaluation of Korean Students’ Oral Chinese Fluency Based on Artificial Neural Networks

作　　者：柴省三[1] 鲍杰 CHAI Xing-san;BAO Jie(Beijing Language and Culture University,Beijing 100083)

机构地区：[1]北京语言大学国际学生教育政策与评价研究院,北京100083

出　　处：《汉语学习》2022年第5期72-81,共10页Chinese Language Learning

基　　金：国家社科基金重点项目“基于HSK大数据挖掘的汉语习得研究”(项目编号:17AYY011);北京语言大学重大专项项目“第二语言习得与测试接口研究”(项目编号:19ZDJ04);北京语言大学梧桐创新平台项目(项目编号:18PT10);北京语言大学中国语言文学高精尖学科建设项目一般项目“新时期国际中文在线教育现状调查与评价体系研究”资助。

摘　　要：流利性是衡量二语学习者口语水平高低的重要标准之一。本研究以HSK(高等)口语测试语料为基础,统计了时间、表达和语言三个维度14项口语流利性测量指标,通过人工神经网络考察口语流利性测量指标对口语水平的预测效度。研究结果表明:选取的14项指标中百音节更改次数、T单位正确率、剔除更改音节占比、修正比例、语速这5项指标的标准化贡献率均大于50%,对汉语二语者的口语水平具有较高的预测价值。Fluency is one of the important criteria to measure the oral proficiency of second language learners. Based on the materials of the HSK(Advanced) Speaking Test, this study counts 14 indicators of oral fluency in three dimensions: temporal, performance and linguistics,and examines the predictive validity of indicators on oral proficiency through artificial neural networks. The results show that among the 14 selected indicators, the standardized contribution rate of the five indictors, namely the number of repairs per 100 syllables, the ratio of error-free T-units to total T-units, the ratio of pruned length to total length, the ratio of amendments to total repairs and the speech rate are higher than 50%, indicating that this five indicators have a high predictive value for the oral proficiency of Chinese as a second language learners.

关 键 词：口语流利性 口语评价 韩国汉语学习者 人工神经网络 

分 类 号：H195.3[语言文字—汉语]