Glottal and vocal tract characteristics of voice impersonators

Voice impersonators possess a flexible voice which allows them to imitate and create different voice identities. These impersonations present a challenge for forensic analysis and speaker identification systems. To better understand the phenomena underlying successful voice impersonation, we collect...

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Main Authors: Marziliano, Pina, German, James Sneed, Amin, Talal B.
Other Authors: School of Electrical and Electronic Engineering
Format: Article
Language:English
Published: 2014
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Online Access:https://hdl.handle.net/10356/103615
http://hdl.handle.net/10220/19264
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1036152020-03-07T14:00:37Z Glottal and vocal tract characteristics of voice impersonators Marziliano, Pina German, James Sneed Amin, Talal B. School of Electrical and Electronic Engineering School of Humanities and Social Sciences DRNTU::Engineering::Electrical and electronic engineering::Electronic apparatus and materials Voice impersonators possess a flexible voice which allows them to imitate and create different voice identities. These impersonations present a challenge for forensic analysis and speaker identification systems. To better understand the phenomena underlying successful voice impersonation, we collected a database of synchronous speech and ElectroGlottoGraphic (EGG) signals from three voice impersonators each producing nine distinct voice identities. We analyzed glottal and vocal tract measures including F0, speech rate, vowel formant frequencies, and timing characteristics of the vocal folds. Our analysis confirmed that the impersonators modulated all four parameters in producing the voices, and provides a lower bound on the scale of variability that is available to impersonators. Importantly, vowel formant differences across voices were highly dependent on vowel category, showing that such effects cannot be captured by global transformations that ignore the linguistic parse. We address this issue through the development of a no-reference objective metric based on the vowel-dependent variance of the formants associated with each voice. This metric both ranks the impersonators natural voices highly, and correlates strongly with the results of a subjective listening test. Together, these results demonstrate the utility of voice variability data for the development of voice disguise detection and speaker identification applications. Accepted version 2014-04-24T02:09:45Z 2019-12-06T21:16:20Z 2014-04-24T02:09:45Z 2019-12-06T21:16:20Z 2014 2014 Journal Article Amin, T. B., Marziliano, P., & German, J. S. (2014). Glottal and Vocal Tract Characteristics of Voice Impersonators. IEEE Transactions on Multimedia, 16(3), 668-678. 1520-9210 https://hdl.handle.net/10356/103615 http://hdl.handle.net/10220/19264 10.1109/TMM.2014.2300071 177789 en IEEE transactions on multimedia © 2014 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. The published version is available at: [http://dx.doi.org/10.1109/TMM.2014.2300071]. application/pdf
institution Nanyang Technological University
building NTU Library
country Singapore
collection DR-NTU
language English
topic DRNTU::Engineering::Electrical and electronic engineering::Electronic apparatus and materials
spellingShingle DRNTU::Engineering::Electrical and electronic engineering::Electronic apparatus and materials
Marziliano, Pina
German, James Sneed
Amin, Talal B.
Glottal and vocal tract characteristics of voice impersonators
description Voice impersonators possess a flexible voice which allows them to imitate and create different voice identities. These impersonations present a challenge for forensic analysis and speaker identification systems. To better understand the phenomena underlying successful voice impersonation, we collected a database of synchronous speech and ElectroGlottoGraphic (EGG) signals from three voice impersonators each producing nine distinct voice identities. We analyzed glottal and vocal tract measures including F0, speech rate, vowel formant frequencies, and timing characteristics of the vocal folds. Our analysis confirmed that the impersonators modulated all four parameters in producing the voices, and provides a lower bound on the scale of variability that is available to impersonators. Importantly, vowel formant differences across voices were highly dependent on vowel category, showing that such effects cannot be captured by global transformations that ignore the linguistic parse. We address this issue through the development of a no-reference objective metric based on the vowel-dependent variance of the formants associated with each voice. This metric both ranks the impersonators natural voices highly, and correlates strongly with the results of a subjective listening test. Together, these results demonstrate the utility of voice variability data for the development of voice disguise detection and speaker identification applications.
author2 School of Electrical and Electronic Engineering
author_facet School of Electrical and Electronic Engineering
Marziliano, Pina
German, James Sneed
Amin, Talal B.
format Article
author Marziliano, Pina
German, James Sneed
Amin, Talal B.
author_sort Marziliano, Pina
title Glottal and vocal tract characteristics of voice impersonators
title_short Glottal and vocal tract characteristics of voice impersonators
title_full Glottal and vocal tract characteristics of voice impersonators
title_fullStr Glottal and vocal tract characteristics of voice impersonators
title_full_unstemmed Glottal and vocal tract characteristics of voice impersonators
title_sort glottal and vocal tract characteristics of voice impersonators
publishDate 2014
url https://hdl.handle.net/10356/103615
http://hdl.handle.net/10220/19264
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