Speaker Recognition Exploiting D2D Communications Paradigm: Performance Evaluation of Multiple Observations Approaches

Speaker Recognition Exploiting D2D Communications Paradigm: Performance Evaluation of Multiple... The diffusion of Device-to-Device (D2D) communications opens the door to exploit the contributions of multiple Mobile Devices (MDs) to accomplish collaborative tasks. In this paper a speaker recognition algorithm for MDs based on a multiple-observations approach is presented. We propose various fusion and clustering algorithms aimed at efficiently exploiting data coming from MDs. Numerical results show that in many cases our multiple-observation approach is able to significantly improve the accuracy of the considered speaker recognition algorithm. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Mobile Networks and Applications Springer Journals

Speaker Recognition Exploiting D2D Communications Paradigm: Performance Evaluation of Multiple Observations Approaches

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Publisher
Springer US
Copyright
Copyright © 2017 by Springer Science+Business Media New York
Subject
Engineering; Communications Engineering, Networks; Computer Communication Networks; Electrical Engineering; IT in Business
ISSN
1383-469X
eISSN
1572-8153
D.O.I.
10.1007/s11036-017-0876-z
Publisher site
See Article on Publisher Site

Abstract

The diffusion of Device-to-Device (D2D) communications opens the door to exploit the contributions of multiple Mobile Devices (MDs) to accomplish collaborative tasks. In this paper a speaker recognition algorithm for MDs based on a multiple-observations approach is presented. We propose various fusion and clustering algorithms aimed at efficiently exploiting data coming from MDs. Numerical results show that in many cases our multiple-observation approach is able to significantly improve the accuracy of the considered speaker recognition algorithm.

Journal

Mobile Networks and ApplicationsSpringer Journals

Published: May 18, 2017

References

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