On the optimum speech segment length for depression detection

• Main Authors: Alghifari, Muhammad Fahreza, Gunawan, Teddy Surya, Wan Nordin, Mimi Aminah, Kartiwi, Mira, Borhan, Lihanna
• Format: Conference or Workshop Item
• Language: English; English
• Published: IEEE 2019
• Subjects: T Technology (General)
• Online Access: http://irep.iium.edu.my/80387/1/80387%20On%20the%20Optimum%20Speech%20Segment%20Length.pdf; http://irep.iium.edu.my/80387/2/80387%20On%20the%20Optimum%20Speech%20Segment%20Length%20%20SCOPUS.pdf; http://irep.iium.edu.my/80387/; https://ieeexplore.ieee.org/document/9057319

Depression is a worldwide problem, which according to the World Health Organization, is the largest contributor to global disability. According to a study, around 18336 Malaysians are suffering from depression. Therefore, an automated system that can detect depression from human speech is needed. Th...