A hybrid approach to assessing spoken fluency combining three metrics with support vector machines

摘要：

Utilizing Pearson-r correlations and Support Vector Machine (SVM) analyses, this paper provides specific evidence regarding the extent to which the interface between human and computer evaluations of spontaneous engaged speech provide statistically significant measures of fluency. Three types of measures are used: quantitative measures, common sense notional measures, and comprehensive measures. As such, it contributes to the growing body of literature describing the current limits of automatic systems for evaluating spoken proficiency, it supports the continued development and implementation of hybrid systems, and it includes suggestions for the utilization of additional automatic analyses within a hybrid system.

关键词： spoken proficiency computer analysis human perception Pearson-r correlation support vector machine (SVM) hybrid system

作者: Garrett Molholt Li Liao

作者单位: English Dept. West Chester University of Pennsylvania, West Chester, PA 193 80, USA Computer and Information Sciences, University of Delaware, Newark, DE 19716, USA

会议类型: 国际会议

会议名称: 2011 4th International Conference on Biomedical Engineering and Informatics(第四届生物医学工程与信息学国际会议 BMEI 2011)

会议地点: 上海

会议语种:英文

页码: 2236-2239

在线出版日期: 2011-10-15（万方平台首次上网日期，不代表论文的发表时间）