Detection of mood disorder using speech emotion profiles and LSTM

Tsung Hsien Yang, Chung Hsien Wu, Kun Yi Huang, Ming Hsiang Su

研究成果: Conference contribution

10 引文 斯高帕斯(Scopus)

摘要

In mood disorder diagnosis, bipolar disorder (BD) patients are often misdiagnosed as unipolar depression (UD) on initial presentation. It is crucial to establish an accurate distinction between BD and UD to make a correct and early diagnosis, leading to improvements in treatment and course of illness. To deal with this misdiagnosis problem, in this study, we experimented on eliciting subjects' emotions by watching six eliciting emotional video clips. After watching each video clips, their speech responses were collected when they were interviewing with a clinician. In mood disorder detection, speech emotions play an import role to detect manic or depressive symptoms. Therefore, speech emotion profiles (EP) are obtained by using the support vector machine (SVM) which are built via speech features adapted from selected databases using a denoising autoencoder-based method. Finally, a Long Short-Term Memory (LSTM) recurrent neural network is employed to characterize the temporal information of the EPs with respect to six emotional videos. Comparative experiments clearly show the promising advantage and efficacy of the LSTM-based approach for mood disorder detection.

原文English
主出版物標題Proceedings of 2016 10th International Symposium on Chinese Spoken Language Processing, ISCSLP 2016
編輯Hsin-Min Wang, Qingzhi Hou, Yuan Wei, Tan Lee, Jianguo Wei, Lei Xie, Hui Feng, Jianwu Dang, Jianwu Dang
發行者Institute of Electrical and Electronics Engineers Inc.
ISBN(電子)9781509042937
DOIs
出版狀態Published - 2017 五月 2
事件10th International Symposium on Chinese Spoken Language Processing, ISCSLP 2016 - Tianjin, China
持續時間: 2016 十月 172016 十月 20

出版系列

名字Proceedings of 2016 10th International Symposium on Chinese Spoken Language Processing, ISCSLP 2016

Other

Other10th International Symposium on Chinese Spoken Language Processing, ISCSLP 2016
國家/地區China
城市Tianjin
期間16-10-1716-10-20

All Science Journal Classification (ASJC) codes

  • 訊號處理
  • 電腦視覺和模式識別
  • 語言和語言學

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