Re-examining the robustness of voice features in predicting depression: Compared with baseline of confounders | |
Pan, Wei1,2; Flint, Jonathan3; Shenhav, Liat4; Liu, Tianli5; Liu, Mingming1,2; Hu, Bin6; Zhu, Tingshao1 | |
第一作者 | Pan, Wei |
通讯作者邮箱 | tszhu@psych.ac.cn |
心理所单位排序 | 1 |
摘要 | A large proportion of Depression Disorder patients do not receive an effective diagnosis, which makes it necessary to find a more objective assessment to facilitate a more rapid and accurate diagnosis of depression. Speech data is easy to acquire clinically, its association with depression has been studied, although the actual predictive effect of voice features has not been examined. Thus, we do not have a general understanding of the extent to which voice features contribute to the identification of depression. In this study, we investigated the significance of the association between voice features and depression using binary logistic regression, and the actual classification effect of voice features on depression was re-examined through classification modeling. Nearly 1000 Chinese females participated in this study. Several different datasets was included as test set. We found that 4 voice features (PC1, PC6, PC17, PC24, P<0.05, corrected) made significant contribution to depression, and that the contribution effect of the voice features alone reached 35.65% (Nagelkerke's R-2). In classification modeling, voice data based model has consistently higher predicting accuracy(F-measure) than the baseline model of demographic data when tested on different datasets, even across different emotion context. F-measure of voice features alone reached 81%, consistent with existing data. These results demonstrate that voice features are effective in predicting depression and indicate that more sophisticated models based on voice features can be built to help in clinical diagnosis. |
2019-06-20 | |
DOI | 10.1371/journal.pone.0218172 |
发表期刊 | PLOS ONE |
ISSN | 1932-6203 |
卷号 | 14期号:6页码:14 |
收录类别 | SCI |
资助项目 | National Basic Research Program of China[2014CB744600] |
出版者 | PUBLIC LIBRARY SCIENCE |
WOS关键词 | HAN CHINESE WOMEN ; CLINICAL DEPRESSION ; MENTAL-DISORDERS ; FIELD TRIALS ; SPEECH ; EMOTION ; BURDEN ; CLASSIFICATION ; EPIDEMIOLOGY ; DISABILITY |
WOS研究方向 | Science & Technology - Other Topics |
WOS类目 | Multidisciplinary Sciences |
WOS记录号 | WOS:000484893500028 |
WOS分区 | Q2 |
资助机构 | National Basic Research Program of China |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.psych.ac.cn/handle/311026/29828 |
专题 | 社会与工程心理学研究室 |
通讯作者 | Zhu, Tingshao |
作者单位 | 1.Chinese Acad Sci, Inst Psychol, Beijing, Peoples R China 2.Univ Chinese Acad Sci, Beijing, Peoples R China 3.Univ Calif Los Angeles, Semel Inst Neurosci & Human Behav, Ctr Neurobehav Genet, Los Angeles, CA 90024 USA 4.Univ Calif Los Angeles, Dept Comp Sci, Los Angeles, CA 90024 USA 5.Peking Univ, Inst Populat Res, Beijing, Peoples R China 6.Lanzhou Univ, Sch Informat Sci & Engn, Lanzhou, Gansu, Peoples R China |
第一作者单位 | 中国科学院心理研究所 |
通讯作者单位 | 中国科学院心理研究所 |
推荐引用方式 GB/T 7714 | Pan, Wei,Flint, Jonathan,Shenhav, Liat,et al. Re-examining the robustness of voice features in predicting depression: Compared with baseline of confounders[J]. PLOS ONE,2019,14(6):14. |
APA | Pan, Wei.,Flint, Jonathan.,Shenhav, Liat.,Liu, Tianli.,Liu, Mingming.,...&Zhu, Tingshao.(2019).Re-examining the robustness of voice features in predicting depression: Compared with baseline of confounders.PLOS ONE,14(6),14. |
MLA | Pan, Wei,et al."Re-examining the robustness of voice features in predicting depression: Compared with baseline of confounders".PLOS ONE 14.6(2019):14. |
条目包含的文件 | ||||||
文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
Re-examining the rob(557KB) | 期刊论文 | 出版稿 | 限制开放 | CC BY-NC-SA | 请求全文 |
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