Classifications of clinical depression detection using acoustic measures in Malay speakers

—Objective screening mechanism using paralinguistic cues to enhance current diagnostic on detecting depression is desirable, which resulted in the rise of research on this area. However, to date, there has been no research done using dataset of Malay speakers. This paper presented an acoustic depre...

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Main Authors: Azam, Huda, Nik Hashim, Nik Nur Wahidah, Sediono, Wahju, Mukhtar, Firdaus, Ibrahim, Normala, Syed Mokhtar, Syarifah Suziah, Abdul Aziz, Salina
Format: Proceeding Paper
Language:English
English
Published: Institute of Electrical and Electronics Engineers Inc. 2016
Subjects:
Online Access:http://irep.iium.edu.my/56813/
http://irep.iium.edu.my/56813/1/56813_Classifications%20of%20clinical%20depression_complete.pdf
http://irep.iium.edu.my/56813/13/56813_Classifications%20of%20clinical%20depression_SCOPUS.pdf
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author Azam, Huda
Nik Hashim, Nik Nur Wahidah
Sediono, Wahju
Mukhtar, Firdaus
Ibrahim, Normala
Syed Mokhtar, Syarifah Suziah
Abdul Aziz, Salina
author_facet Azam, Huda
Nik Hashim, Nik Nur Wahidah
Sediono, Wahju
Mukhtar, Firdaus
Ibrahim, Normala
Syed Mokhtar, Syarifah Suziah
Abdul Aziz, Salina
author_sort Azam, Huda
building IIUM Repository
collection Online Access
description —Objective screening mechanism using paralinguistic cues to enhance current diagnostic on detecting depression is desirable, which resulted in the rise of research on this area. However, to date, there has been no research done using dataset of Malay speakers. This paper presented an acoustic depression detection classification using Linear and Quadratic Discriminant analysis with transition parameters and power spectral density as the acoustic features. Among the two features, power spectral density performed better, especially with the combination of band 1, 2 and 3 for both male and female data. As for the Transition parameters, we found that unvoiced feature performed best overall for both male and female.
first_indexed 2025-11-14T16:43:11Z
format Proceeding Paper
id iium-56813
institution International Islamic University Malaysia
institution_category Local University
language English
English
last_indexed 2025-11-14T16:43:11Z
publishDate 2016
publisher Institute of Electrical and Electronics Engineers Inc.
recordtype eprints
repository_type Digital Repository
spelling iium-568132019-12-03T11:39:44Z http://irep.iium.edu.my/56813/ Classifications of clinical depression detection using acoustic measures in Malay speakers Azam, Huda Nik Hashim, Nik Nur Wahidah Sediono, Wahju Mukhtar, Firdaus Ibrahim, Normala Syed Mokhtar, Syarifah Suziah Abdul Aziz, Salina QP Physiology RF Otorhinolaryngology TK Electrical engineering. Electronics Nuclear engineering —Objective screening mechanism using paralinguistic cues to enhance current diagnostic on detecting depression is desirable, which resulted in the rise of research on this area. However, to date, there has been no research done using dataset of Malay speakers. This paper presented an acoustic depression detection classification using Linear and Quadratic Discriminant analysis with transition parameters and power spectral density as the acoustic features. Among the two features, power spectral density performed better, especially with the combination of band 1, 2 and 3 for both male and female data. As for the Transition parameters, we found that unvoiced feature performed best overall for both male and female. Institute of Electrical and Electronics Engineers Inc. 2016 Proceeding Paper PeerReviewed application/pdf en http://irep.iium.edu.my/56813/1/56813_Classifications%20of%20clinical%20depression_complete.pdf application/pdf en http://irep.iium.edu.my/56813/13/56813_Classifications%20of%20clinical%20depression_SCOPUS.pdf Azam, Huda and Nik Hashim, Nik Nur Wahidah and Sediono, Wahju and Mukhtar, Firdaus and Ibrahim, Normala and Syed Mokhtar, Syarifah Suziah and Abdul Aziz, Salina (2016) Classifications of clinical depression detection using acoustic measures in Malay speakers. In: 2016 IEEE EMBS Conference on Biomedical Engineering and Sciences (IECBES), 04 Dec - 08 Dec 2016, Hotel Pullman Kuala Lumpur. https://www.ieee.org/conferences_events/conferences/conferencedetails/index.html?Conf_ID=37087 10.1109/IECBES.2016.7843521
spellingShingle QP Physiology
RF Otorhinolaryngology
TK Electrical engineering. Electronics Nuclear engineering
Azam, Huda
Nik Hashim, Nik Nur Wahidah
Sediono, Wahju
Mukhtar, Firdaus
Ibrahim, Normala
Syed Mokhtar, Syarifah Suziah
Abdul Aziz, Salina
Classifications of clinical depression detection using acoustic measures in Malay speakers
title Classifications of clinical depression detection using acoustic measures in Malay speakers
title_full Classifications of clinical depression detection using acoustic measures in Malay speakers
title_fullStr Classifications of clinical depression detection using acoustic measures in Malay speakers
title_full_unstemmed Classifications of clinical depression detection using acoustic measures in Malay speakers
title_short Classifications of clinical depression detection using acoustic measures in Malay speakers
title_sort classifications of clinical depression detection using acoustic measures in malay speakers
topic QP Physiology
RF Otorhinolaryngology
TK Electrical engineering. Electronics Nuclear engineering
url http://irep.iium.edu.my/56813/
http://irep.iium.edu.my/56813/
http://irep.iium.edu.my/56813/
http://irep.iium.edu.my/56813/1/56813_Classifications%20of%20clinical%20depression_complete.pdf
http://irep.iium.edu.my/56813/13/56813_Classifications%20of%20clinical%20depression_SCOPUS.pdf