TY  - JOUR
PY  - 2022//
TI  - Detectionof major depressive disorder based on a combination of voice features: an exploratory approach
JO  - International journal of environmental research and public health
A1  - Higuchi, Masakazu
A1  - Nakamura, Mitsuteru
A1  - Shinohara, Shuji
A1  - Omiya, Yasuhiro
A1  - Takano, Takeshi
A1  - Mizuguchi, Daisuke
A1  - Sonota, Noriaki
A1  - Toda, Hiroyuki
A1  - Saito, Taku
A1  - So, Mirai
A1  - Takayama, Eiji
A1  - Terashi, Hiroo
A1  - Mitsuyoshi, Shunji
A1  - Tokuno, Shinichi
SP  - e11397
EP  - e11397
VL  - 19
IS  - 18
N2  - In general, it is common knowledge that people's feelings are reflected in their voice and facial expressions. This research work focuses on developing techniques for diagnosing depression based on acoustic properties of the voice. In this study, we developed a composite index of vocal acoustic properties that can be used for depression detection. Voice recordings were collected from patients undergoing outpatient treatment for major depressive disorder at a hospital or clinic following a physician's diagnosis. Numerous features were extracted from the collected audio data using openSMILE software. Furthermore, qualitatively similar features were combined using principal component analysis. The resulting components were incorporated as parameters in a logistic regression based classifier, which achieved a diagnostic accuracy of ~90% on the training set and ~80% on the test set. Lastly, the proposed metric could serve as a new measure for evaluation of major depressive disorder.<p />  <p>Language: en</p>
LA  - en
SN  - 1661-7827
UR  - http://dx.doi.org/10.3390/ijerph191811397
ID  - ref1
ER  -