The Role of Language in Building Automatic Models for Depression Detection-Reference-Cited by-同舟云学术

The Role of Language in Building Automatic Models for Depression Detection

Published:2022-09-12 Issue: Volume: Page:
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Container-title:2022 IEEE Intl Conf on Dependable, Autonomic and Secure Computing, Intl Conf on Pervasive Intelligence and Computing, Intl Conf on Cloud and Big Data Computing, Intl Conf on Cyber Science and Technology Congress (DASC/PiCom/CBDCom/CyberSciTech)
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Author:

Raimo Gennaro¹,Conson Massimiliano¹,Amorese Terry¹,Cuciniello Marialucia¹,Greco Claudia¹,Cordasco Gennaro¹,Carrion Zoraida Callejas²,Glackin Cornelius³,Esposito Anna¹

Affiliation:

1. Università Della Campania "L. Vanvitelli",Dept. of Psychology,Caserta,Italy

2. University of Granada,Dept. of Software Engineering,Granada,Spain

3. Intelligent Voice Ltd,London,England

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9927523/9927699/09927925.pdf?arnumber=9927925

Reference34 articles.

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2. Global, regional, and national burden of 12 mental disorders in 204 countries and territories, 1990–2019: a systematic analysis for the global burden of disease study 2019;The Lancet Psychiatry,2022

3. Depression and everyday social activity, belonging, and well-being.

4. Ibm corp. released 2013. ibm spss statistics for windows, version 25.0. armonk, ny: Ibm corp;statistics;Google search,2013

5. A Lightweight Machine Learning Approach to Detect Depression from Speech Analysis

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1. Bio-acoustic features of depression: A review;Biomedical Signal Processing and Control;2023-08