Privacy preserving encrypted phonetic search of speech data

Glackin, C., Chollet, G., Dugan, N., Cannings, N., Wall, J., Tahir, S. F., Ray, I. G. & Rajarajan, M. (2017). Privacy preserving encrypted phonetic search of speech data. 2017 IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, pp. 6414-6418. doi: 10.1109/ICASSP.2017.7953391

[img]
Preview
Text - Accepted Version
Download (509kB) | Preview

Abstract

This paper presents a strategy for enabling speech recognition to be performed in the cloud whilst preserving the privacy of users. The approach advocates a demarcation of responsibilities between the client and server-side components for performing the speech recognition task. On the client-side resides the acoustic model, which symbolically encodes the audio and encrypts the data before uploading to the server. The server-side then employs searchable encryption to enable the phonetic search of the speech content. Some preliminary results for speech encoding and searchable encryption are presented.

Item Type: Article
Additional Information: © 2017 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.
Uncontrolled Keywords: Speech recognition, privacy, searchable encryption, GPGPU computing
Divisions: School of Engineering & Mathematical Sciences > Engineering
URI: http://openaccess.city.ac.uk/id/eprint/18491

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year

View more statistics