A novel framework for distress detection through an automated speech processing system

Rana, Rajib and Gururajan, Raj ORCID: https://orcid.org/0000-0002-5919-0174 and Mackenzie, Geraldine and Dunn, Jeff and Gray, Anthony and Zhou, Xujuan and Barua, Prabal Datta and Epps, Julien and Humphris, Gerald Michael (2018) A novel framework for distress detection through an automated speech processing system. In: 2018 IEEE/WIC/ACM International Conference on Web Intelligence (WI 2018), 3-6 Dec 2018, Santiago, Chile.

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Based on our ongoing work, this work in progress project aims to develop an automated system to detect distress in people to enable early referral for interventions to target anxiety and depression, to mitigate suicidal ideation and to improve adherence to treatment. The project will utilize either use existing voice data to assess people into various scales of distress, or will collect voice data as per existing standards of distress measurement, to develop basic computing algorithms required to detect various attributes associated with distress, detected through a person’s voice in a telephone call to a helpline. This will be then matched with the already available psychological assessment instruments such as the Distress Thermometer for these persons. In order to trigger interventions, organizational contexts are essential as interventions rely on the type of distress. Therefore, the model will be tested on various organizational settings such as the Police, Emergency and Health along with the Distress detection instruments normally used in a psychological assessment for accuracy and validation. The outcome of the project will culminate in a fully automated integrated system, and will save significant resources to organizations. The translation of the project will be realized in step-change improvements to quality of life within the gamut of public policy.

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Item Type: Conference or Workshop Item (Commonwealth Reporting Category E) (Paper)
Refereed: Yes
Item Status: Live Archive
Additional Information: © 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Faculty/School / Institute/Centre: Current - Institute for Resilient Regions
Faculty/School / Institute/Centre: Current - Institute for Resilient Regions
Date Deposited: 18 Feb 2019 02:05
Last Modified: 07 Jun 2021 02:40
Uncontrolled Keywords: speech recognition, distress identification, public policy
Fields of Research (2008): 08 Information and Computing Sciences > 0801 Artificial Intelligence and Image Processing > 080109 Pattern Recognition and Data Mining
11 Medical and Health Sciences > 1117 Public Health and Health Services > 111714 Mental Health
Fields of Research (2020): 46 INFORMATION AND COMPUTING SCIENCES > 4602 Artificial intelligence > 460212 Speech recognition
Socio-Economic Objectives (2008): E Expanding Knowledge > 97 Expanding Knowledge > 970108 Expanding Knowledge in the Information and Computing Sciences
Identification Number or DOI: https://doi.org/10.1109/WI.2018.00-29
URI: http://eprints.usq.edu.au/id/eprint/35664

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