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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Digital Signal Proce...arrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
Digital Signal Processing
Article . 2015 . Peer-reviewed
License: Elsevier TDM
Data sources: Crossref
DBLP
Article . 2015
Data sources: DBLP
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Verification of hidden speaker behind transformation disguised voices

Authors: Yong Wang; Haojun Wu; Jiwu Huang;

Verification of hidden speaker behind transformation disguised voices

Abstract

We investigate the effects of voice transformation disguise on ASV performance.We propose an algorithm to estimate transformation factor.We propose an algorithm to restore the genuine acoustic characteristics.We integrate the above algorithms into GMM-UBM based ASV system.The proposed approach achieves 3-4% EER. Voice transformation, which has been integrated in many audio (speech) processing tools, is a common operation to change a person's voice and to conceal his or her identity. It can deceive human beings and automatic speaker verification (ASV) systems easily, and thus it presents threats to security. Until now, few efforts have been reported on the recognition of hidden speakers from such disguised voices. In this paper, we propose concrete countermeasures to erase the disguise effects and verify the speaker's identity from voice transformation disguised voices. The proposed system is tested by commonly used audio editors and voice transformation algorithms. The experimental results show that the performances of baseline ASV system without our proposed countermeasures are entirely destroyed by voice transformation disguise with equal error rates (EERs) higher than 40%; while with our proposed countermeasures, the verification performances are improved significantly with EERs lowered to 3%-4%.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
7
Top 10%
Average
Average
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