NDLI: A study of acoustic features for depression detection

Content Provider	IEEE Xplore Digital Library
Author	Lopez-Otero, P. Dacia-Fernandez, L. Garcia-Mateo, C.
Copyright Year	2014
Description	Author affiliation: Multimedia Technol. Group (GTM), Univ. de Vigo (Spain), Spain (Lopez-Otero, P.; Dacia-Fernandez, L.; Garcia-Mateo, C.)
Abstract	Clinical depression can be considered as a soft biometric trait that can help to characterize an individual. This mood disorder can be involved in forensic psychological assessment, due to its relevance in different legal issues. The automatic detection of depressed speech has been object of research in the last years, resulting in different algorithmic approaches and acoustic features. Due to the use of different algorithms, databases and performance measures, deciding which ones are more suitable for this task is difficult. In this work, the performance of different acoustic features for depression detection was explored in a common framework. To do so, a depression estimation approach in which the audio data is segmented and projected into a total variability subspace was used, and these projected data was used to estimate the depression level by performing support vector regression. The data and evaluation metrics were the ones used in the audiovisual emotion challenge (AVEC 2013).
Starting Page	1
Ending Page	6
File Size	194198
Page Count	6
File Format	PDF
ISBN	9781479943708
DOI	10.1109/IWBF.2014.6914245
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-03-27
Publisher Place	Malta
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Training Depression detection Speaker profiling IVectors Feature extraction Speech Vectors Mel frequency cepstral coefficient Speech features Testing
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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