Development of sorrow analysis dataset for speech depression prediction

Alghifari, Muhammad Fahreza and Gunawan, Teddy Surya and Kartiwi, Mira (2023) Development of sorrow analysis dataset for speech depression prediction. In: 2023 IEEE International Instrumentation and Measurement Technology Conference, I2MTC 2023, 22-25 May 2023, Kuala Lumpur, Malaysia.

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Abstract

Computers can get insight into the user's mental state, including depression prediction, by analyzing speech signals. Numerous uses exist, ranging from customer service to depression-related suicide prevention. In this study, we proposed a novel depression detection method based on deep learning. Deep neural network variants, 1D-CNN, 2D-CNN, and BiLSTM, were utilized. This research developed a new speech depression dataset, namely the Sorrow Analysis Dataset. It is an English depression audio dataset of 64 recordings of depressed and non-depressed individuals. Results showed that of the various architectures tested, 1D-CNN was found to produce the highest average accuracy of 97% with 5-fold validation.

Item Type:	Proceeding Paper (Invited Papers)
Additional Information:	Muhammad Fahreza is the PG student using gmail. Dr. Teddy is the first IIUM author using iium email (corresponding author)
Uncontrolled Keywords:	Speech depression dataset, deep learning, CNN, BiLSTM, and k-fold validation.
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7800 Electronics. Computer engineering. Computer hardware. Photoelectronic devices > TK7885 Computer engineering
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button):	Kulliyyah of Engineering > Department of Electrical and Computer Engineering Kulliyyah of Information and Communication Technology > Department of Information System Kulliyyah of Information and Communication Technology > Department of Information System Kulliyyah of Engineering Kulliyyah of Information and Communication Technology Kulliyyah of Information and Communication Technology
Depositing User:	Prof. Dr. Teddy Surya Gunawan
Date Deposited:	09 Jan 2024 12:07
Last Modified:	09 Jan 2024 12:07
URI:	http://irep.iium.edu.my/id/eprint/109824

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