Detecting Depression Using an Ensemble Logistic Regression Model Based on Multiple Speech Features
المؤلفون المشاركون
Wang, Gang
Jiang, Haihua
Hu, Bin
Liu, Zhenyu
Zhang, Lan
Li, Xiaoyu
Kang, Huanyu
المصدر
Computational and Mathematical Methods in Medicine
العدد
المجلد 2018، العدد 2018 (31 ديسمبر/كانون الأول 2018)، ص ص. 1-9، 9ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2018-09-24
دولة النشر
مصر
عدد الصفحات
9
التخصصات الرئيسية
الملخص EN
Early intervention for depression is very important to ease the disease burden, but current diagnostic methods are still limited.
This study investigated automatic depressed speech classification in a sample of 170 native Chinese subjects (85 healthy controls and 85 depressed patients).
The classification performances of prosodic, spectral, and glottal speech features were analyzed in recognition of depression.
We proposed an ensemble logistic regression model for detecting depression (ELRDD) in speech.
The logistic regression, which was superior in recognition of depression, was selected as the base classifier.
This ensemble model extracted many speech features from different aspects and ensured diversity of the base classifier.
ELRDD provided better classification results than the other compared classifiers.
A technique for identifying depression based on ELRDD, ELRDD-E, was here suggested and tested.
It offered encouraging outcomes, revealing a high accuracy level of 75.00% for females and 81.82% for males, as well as an advantageous sensitivity/specificity ratio of 79.25%/70.59% for females and 78.13%/85.29% for males.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Jiang, Haihua& Hu, Bin& Liu, Zhenyu& Wang, Gang& Zhang, Lan& Li, Xiaoyu…[et al.]. 2018. Detecting Depression Using an Ensemble Logistic Regression Model Based on Multiple Speech Features. Computational and Mathematical Methods in Medicine،Vol. 2018, no. 2018, pp.1-9.
https://search.emarefa.net/detail/BIM-1132093
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Jiang, Haihua…[et al.]. Detecting Depression Using an Ensemble Logistic Regression Model Based on Multiple Speech Features. Computational and Mathematical Methods in Medicine No. 2018 (2018), pp.1-9.
https://search.emarefa.net/detail/BIM-1132093
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Jiang, Haihua& Hu, Bin& Liu, Zhenyu& Wang, Gang& Zhang, Lan& Li, Xiaoyu…[et al.]. Detecting Depression Using an Ensemble Logistic Regression Model Based on Multiple Speech Features. Computational and Mathematical Methods in Medicine. 2018. Vol. 2018, no. 2018, pp.1-9.
https://search.emarefa.net/detail/BIM-1132093
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1132093
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر