基于语音识别的学生学习风格挖掘研究  

Research on Mining Learning Styles of Students Using Speech Recognition

作　　者：周海波[1] ZHOU Haibo(Yancheng College of Mechatronic Technology,Yancheng 224001,China)

机构地区：[1]盐城机电高等职业技术学校,江苏盐城224001

出　　处：《电声技术》2025年第2期95-97,共3页Audio Engineering

摘　　要：基于语音识别技术,探讨如何挖掘学生的学习风格。通过智能学习平台实时采集学生的语音信号,并采用支持向量机(Support Vector Machine,SVM)算法对语音特征进行分析,识别学生的学习风格类型。实验结果显示,语音识别技术在学习风格分类中的语音识别准确率接近100%,有助于为每种学习风格的学生提供个性化的教学方案。研究表明,语音识别技术为个性化教育提供了新的技术支持,能够提升学习效果并满足学生的多样化需求。Based on speech recognition technology,this paper discusses how to tap students' learning style.Students' voice signals are collected in real time through the intelligent learning platform,and the voice features are analyzed by using the Support Vector Machine(SVM) algorithm to identify the types of students' learning styles.The experimental results show that the accuracy of speech recognition technology in learning style classification is close to 100%,which is helpful to provide personalized teaching programs for students with each learning style.The research shows that speech recognition technology provides new technical support for personalized education,which can improve the learning effect and meet the diverse needs of students.

关 键 词：语音识别 学生 学习风格 挖掘 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]