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Detecting postpartum depression in depressed people by speech features
Wang, Jingying1,2; Sui, Xiaoyun1; Hu, Bin3; Flint, Jonathan4; Bai, Shuotian5; Gao, Yuanbo2; Zhou, Yang1,2; Zhu, Tingshao1
第一作者Wang, Jingying
2018
会议名称3rd International Conference on Human Centered Computing, HCC 2017
通讯作者邮箱tszhu@psych.ac.cn
会议录名称Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
卷号10745 LNCS
页码433-442
会议日期August 7, 2017 - August 9, 2017
会议地点Kazan
会议举办国Russia
出版者Springer Verlag
产权排序1
摘要

Postpartum depression (PPD) is a depressive disorder with peripartum onset, which brings heavy burden to individuals and their families. In this paper, we propose to detect PPD in depressed people via voices. We used openSMILE for feature extraction, selected Sequential Floating Forward Selection (SFFS) algorithm for feature selection, tried different settings of features, set 5-fold cross validation and applied Support Vector Machine (SVM) on Weka for training and testing different models. The best predictive performance among our models is 69%, which suggests that the speech features could be used as a potential behavioral indicator for identifying PPD in depression. We also found that a combined impact of features and content of questions contribute to the prediction. After dimension reduction, the average value of F-measure was increased 5.2%, and the precision of PPD was rose to 75%. Comparing with demographic questions, the features of emotional induction questions have better predictive effects. © Springer International Publishing AG 2018.

学科领域Feature Extraction
DOI10.1007/978-3-319-74521-3_46
ISBN号03029743
收录类别EI
语种英语
EI主题词Classification (Of Information) - Speech Recognition - Support Vector Machines
引用统计
文献类型会议论文
条目标识符http://ir.psych.ac.cn/handle/311026/27752
专题中国科学院行为科学重点实验室
作者单位1.Institute of Psychology, Chinese Academy of Sciences, Beijing; 100101, China;
2.University of Chinese Academy of Sciences, Beijing; 100049, China;
3.School of Information Science and Engineering, Lanzhou University, Gansu; 730000, China;
4.Department of Psychiatry and Biobehavioral Sciences, UCLA David Geffen School of Medicine, Los Angeles; CA; 90095, United States;
5.School of Information Engineering, Hubei University of Economics, Wuhan; 430205, China
推荐引用方式
GB/T 7714
Wang, Jingying,Sui, Xiaoyun,Hu, Bin,et al. Detecting postpartum depression in depressed people by speech features[C]:Springer Verlag,2018:433-442.
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