Privacy Enhanced Speech Emotion Communication using Deep Learning Aided Edge Computing

Ali, Hafiz Shehbaz and Hassan, Fakhar ul and Latif, Siddique and Manzoor, Habib Ullah and Qadir, Junaid (2021) Privacy Enhanced Speech Emotion Communication using Deep Learning Aided Edge Computing. In: IEEE International Conference on Communications Workshops (2021), 14 Jun - 23 Jun 2021, Montreal, Canada.


Abstract

Speech emotion sensing in communication networks has a wide range of applications in real life. In these applications, voice data are transmitted from the user to the central server for storage, processing, and decision making. However, speech data contain vulnerable information that can be used maliciously without the user's consent by an eavesdropping adversary. In this work, we present a privacy-enhanced emotion communication system for preserving the user personal information in emotion-sensing applications. We propose the use of an adversarial learning framework that can be deployed at the edge to unlearn the users' private information in the speech representations. These privacy-enhanced representations can be transmitted to the central server for decision making. We evaluate the proposed model on multiple speech emotion datasets and show that the proposed model can hide users' specific demographic information and improve the robustness of emotion identification without significantly impacting performance. To the best of our knowledge, this is the first work on a privacy-preserving framework for emotion sensing in the communication network.


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Item Type: Conference or Workshop Item (Commonwealth Reporting Category E) (Paper)
Refereed: Yes
Item Status: Live Archive
Additional Information: Files associated with this item cannot be displayed due to copyright restrictions.
Faculty/School / Institute/Centre: Historic - Faculty of Health, Engineering and Sciences - School of Sciences (6 Sep 2019 - 31 Dec 2021)
Faculty/School / Institute/Centre: Historic - Faculty of Health, Engineering and Sciences - School of Sciences (6 Sep 2019 - 31 Dec 2021)
Date Deposited: 20 Apr 2022 02:00
Last Modified: 30 May 2022 03:41
Uncontrolled Keywords: emotion communication system, speech emotion recognition, privacy enhanced features, deep learning, edge computing.
Fields of Research (2008): 08 Information and Computing Sciences > 0801 Artificial Intelligence and Image Processing > 080109 Pattern Recognition and Data Mining
08 Information and Computing Sciences > 0801 Artificial Intelligence and Image Processing > 080107 Natural Language Processing
Fields of Research (2020): 46 INFORMATION AND COMPUTING SCIENCES > 4611 Machine learning > 461101 Adversarial machine learning
46 INFORMATION AND COMPUTING SCIENCES > 4611 Machine learning > 461106 Semi- and unsupervised learning
46 INFORMATION AND COMPUTING SCIENCES > 4611 Machine learning > 461103 Deep learning
46 INFORMATION AND COMPUTING SCIENCES > 4611 Machine learning > 461104 Neural networks
Identification Number or DOI: https://doi.org/10.1109/ICCWorkshops50388.2021.9473669
URI: http://eprints.usq.edu.au/id/eprint/45597

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