Research on Automatic Speech Analysis for Teacher’s Q&A in Classroom

Wenquan Chang; Dongxing Li; Zuying Luo

doi:doi:10.11648/j.si.20170503.14

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Research on Automatic Speech Analysis for Teacher’s Q&A in Classroom

Wenquan Chang, Dongxing Li, Zuying Luo

Published in Science Innovation (Volume 5, Issue 3)

Received: 20 April 2017 Accepted: Published: 20 April 2017

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Abstract

Question-and-aswer (Q&A) is the important content of classroom evaluation. In order to meet the needs of large-scale class evaluation, this work uses voice analysis technology to implement exploratory research on automatic Q&A analyse, mainly on speaker recognition based on MFCC Gaussian mixture model and closed/open question identification based on the logistic regression method. The Q&A auto-analysis system developed in this work can perform automatic analyses for several classroom evaluation indexes including Q&A times, speaking durations of the teacher and his students, and the number of open questions and closed questions. For the real classroom teaching video down-loaded from “CCTV network Chinese public class”, both the speaker recognition and closed/open questions identification of this work have obtained satisfied recognition accuracy with recognition rates above 93%.

Published in	Science Innovation (Volume 5, Issue 3)
DOI	10.11648/j.si.20170503.14
Page(s)	144-150
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Classroom Evaluation, Interaction Among a Teacher and Students, Logistic Regression Model, Speaker Recognition

References

[1]	钟启泉.课堂评价的挑战[J].全球教育展望,2012,(01):10-16。
[2]	崔允漷.论课堂观察LICC范式:一种专业的听评课[J].教育研究,2012,(05):79-83。
[3]	郭绍青,张绒,马彦龙.“有效教学”课堂录像分析方法与工具研究[J].电化教育研究,2013,(01):68-72。
[4]	时丽莉.“弗兰德互动分析系统”在课堂教学中的应用[J].首都师范大学学报(社会科学版),2004,(S2):163-165。
[5]	方海光,高辰柱,陈佳.改进型弗兰德斯互动分析系统及其应用[J].中国电化教育,2012,(10):109-113。
[6]	顾小清,王炜.支持教师专业发展的课堂分析技术新探索[J].中国电化教育,2004,(07):18-21。
[7]	Lu Z, Liu B, Shen L. Speech endpoint detection in strong noisy environment based on the Hilbert-Huang Transform [C]// International Conference on Mechatronics and Automation. IEEE, 2009: 4322-4326.
[8]	宋知用.MATLAB在语音信号分析与合成中的应用[M].北京航空航天大学出版社,2013:116-154。
[9]	熊华乔，郑建彬等.基于说话人模型聚类的说话人识别[J].计算机工程与应用.2014,50(02):133-137。
[10]	Zufeng Weng. Lin Li. Donghui Guo. Speaker Recognition Using Weighted Dynamic MFCC Based on GMM [C]. Anti-Counterfeiting Security and Identification in Communication (ASID), 2010(07):18-20.
[11]	胡政权,曾毓敏,宗原,等.说话人识别中MFCC参数提取的改进[J].计算机工程与应用.2014,50(07):217-220。
[12]	Xinxing Ling. Ling Zhan. Hong Zhao. Ping Zhou. Speaker Recognition System Using the Improved GMM-based Clustering Algorithm [C]. Intelligent Computing and Integrated Systems (ICISS), 2010(10):22-24.
[13]	赵力.语音信号处理[M].机械工业出版社,2016:228-230。
[14]	叶立军,周芳丽.基于录像分析背景下的教师提问方式研究[J].教育理论与实践,2012,(05):52-54。
[15]	黄伟.提问与对话:有效教学的入口与路径[M].浙江大学出版社,2016:73-92。
[16]	PeterHarrington,李锐等.机器学习实战[M].人民邮电出版社,2013:73-88。
[17]	Thomson R P. Strategies for effective teaching.[J]. Nln Publ, 1975(16-1538):12-24.

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APA Style

Wenquan Chang, Dongxing Li, Zuying Luo. (2017). Research on Automatic Speech Analysis for Teacher’s Q&A in Classroom. Science Innovation, 5(3), 144-150. https://doi.org/10.11648/j.si.20170503.14

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ACS Style

Wenquan Chang; Dongxing Li; Zuying Luo. Research on Automatic Speech Analysis for Teacher’s Q&A in Classroom. Sci. Innov. 2017, 5(3), 144-150. doi: 10.11648/j.si.20170503.14

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AMA Style

Wenquan Chang, Dongxing Li, Zuying Luo. Research on Automatic Speech Analysis for Teacher’s Q&A in Classroom. Sci Innov. 2017;5(3):144-150. doi: 10.11648/j.si.20170503.14

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@article{10.11648/j.si.20170503.14,
  author = {Wenquan Chang and Dongxing Li and Zuying Luo},
  title = {Research on Automatic Speech Analysis for Teacher’s Q&A in Classroom},
  journal = {Science Innovation},
  volume = {5},
  number = {3},
  pages = {144-150},
  doi = {10.11648/j.si.20170503.14},
  url = {https://doi.org/10.11648/j.si.20170503.14},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.si.20170503.14},
  abstract = {Question-and-aswer (Q&A) is the important content of classroom evaluation. In order to meet the needs of large-scale class evaluation, this work uses voice analysis technology to implement exploratory research on automatic Q&A analyse, mainly on speaker recognition based on MFCC Gaussian mixture model and closed/open question identification based on the logistic regression method. The Q&A auto-analysis system developed in this work can perform automatic analyses for several classroom evaluation indexes including Q&A times, speaking durations of the teacher and his students, and the number of open questions and closed questions. For the real classroom teaching video down-loaded from “CCTV network Chinese public class”, both the speaker recognition and closed/open questions identification of this work have obtained satisfied recognition accuracy with recognition rates above 93%.},
 year = {2017}
}

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TY  - JOUR
T1  - Research on Automatic Speech Analysis for Teacher’s Q&A in Classroom
AU  - Wenquan Chang
AU  - Dongxing Li
AU  - Zuying Luo
Y1  - 2017/04/20
PY  - 2017
N1  - https://doi.org/10.11648/j.si.20170503.14
DO  - 10.11648/j.si.20170503.14
T2  - Science Innovation
JF  - Science Innovation
JO  - Science Innovation
SP  - 144
EP  - 150
PB  - Science Publishing Group
SN  - 2328-787X
UR  - https://doi.org/10.11648/j.si.20170503.14
AB  - Question-and-aswer (Q&A) is the important content of classroom evaluation. In order to meet the needs of large-scale class evaluation, this work uses voice analysis technology to implement exploratory research on automatic Q&A analyse, mainly on speaker recognition based on MFCC Gaussian mixture model and closed/open question identification based on the logistic regression method. The Q&A auto-analysis system developed in this work can perform automatic analyses for several classroom evaluation indexes including Q&A times, speaking durations of the teacher and his students, and the number of open questions and closed questions. For the real classroom teaching video down-loaded from “CCTV network Chinese public class”, both the speaker recognition and closed/open questions identification of this work have obtained satisfied recognition accuracy with recognition rates above 93%.
VL  - 5
IS  - 3
ER  -

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Author Information

Wenquan Chang

College of Information Science and Technology, Beijing Normal University, Beijing, China
Dongxing Li

College of Information Science and Technology, Beijing Normal University, Beijing, China
Zuying Luo

College of Information Science and Technology, Beijing Normal University, Beijing, China

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APA Style

Wenquan Chang, Dongxing Li, Zuying Luo. (2017). Research on Automatic Speech Analysis for Teacher’s Q&A in Classroom. Science Innovation, 5(3), 144-150. https://doi.org/10.11648/j.si.20170503.14

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ACS Style

Wenquan Chang; Dongxing Li; Zuying Luo. Research on Automatic Speech Analysis for Teacher’s Q&A in Classroom. Sci. Innov. 2017, 5(3), 144-150. doi: 10.11648/j.si.20170503.14

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AMA Style

Wenquan Chang, Dongxing Li, Zuying Luo. Research on Automatic Speech Analysis for Teacher’s Q&A in Classroom. Sci Innov. 2017;5(3):144-150. doi: 10.11648/j.si.20170503.14

Copy | Download

@article{10.11648/j.si.20170503.14,
  author = {Wenquan Chang and Dongxing Li and Zuying Luo},
  title = {Research on Automatic Speech Analysis for Teacher’s Q&A in Classroom},
  journal = {Science Innovation},
  volume = {5},
  number = {3},
  pages = {144-150},
  doi = {10.11648/j.si.20170503.14},
  url = {https://doi.org/10.11648/j.si.20170503.14},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.si.20170503.14},
  abstract = {Question-and-aswer (Q&A) is the important content of classroom evaluation. In order to meet the needs of large-scale class evaluation, this work uses voice analysis technology to implement exploratory research on automatic Q&A analyse, mainly on speaker recognition based on MFCC Gaussian mixture model and closed/open question identification based on the logistic regression method. The Q&A auto-analysis system developed in this work can perform automatic analyses for several classroom evaluation indexes including Q&A times, speaking durations of the teacher and his students, and the number of open questions and closed questions. For the real classroom teaching video down-loaded from “CCTV network Chinese public class”, both the speaker recognition and closed/open questions identification of this work have obtained satisfied recognition accuracy with recognition rates above 93%.},
 year = {2017}
}

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TY  - JOUR
T1  - Research on Automatic Speech Analysis for Teacher’s Q&A in Classroom
AU  - Wenquan Chang
AU  - Dongxing Li
AU  - Zuying Luo
Y1  - 2017/04/20
PY  - 2017
N1  - https://doi.org/10.11648/j.si.20170503.14
DO  - 10.11648/j.si.20170503.14
T2  - Science Innovation
JF  - Science Innovation
JO  - Science Innovation
SP  - 144
EP  - 150
PB  - Science Publishing Group
SN  - 2328-787X
UR  - https://doi.org/10.11648/j.si.20170503.14
AB  - Question-and-aswer (Q&A) is the important content of classroom evaluation. In order to meet the needs of large-scale class evaluation, this work uses voice analysis technology to implement exploratory research on automatic Q&A analyse, mainly on speaker recognition based on MFCC Gaussian mixture model and closed/open question identification based on the logistic regression method. The Q&A auto-analysis system developed in this work can perform automatic analyses for several classroom evaluation indexes including Q&A times, speaking durations of the teacher and his students, and the number of open questions and closed questions. For the real classroom teaching video down-loaded from “CCTV network Chinese public class”, both the speaker recognition and closed/open questions identification of this work have obtained satisfied recognition accuracy with recognition rates above 93%.
VL  - 5
IS  - 3
ER  -

Copy | Download