Please use this identifier to cite or link to this item:
https://hdl.handle.net/10356/103615
Title: | Glottal and vocal tract characteristics of voice impersonators | Authors: | Marziliano, Pina German, James Sneed Amin, Talal B. |
Keywords: | DRNTU::Engineering::Electrical and electronic engineering::Electronic apparatus and materials | Issue Date: | 2014 | Source: | 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. | Series/Report no.: | IEEE transactions on multimedia | Abstract: | 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. | URI: | https://hdl.handle.net/10356/103615 http://hdl.handle.net/10220/19264 |
ISSN: | 1520-9210 | DOI: | 10.1109/TMM.2014.2300071 | Schools: | School of Electrical and Electronic Engineering School of Humanities and Social Sciences |
Rights: | © 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]. | Fulltext Permission: | open | Fulltext Availability: | With Fulltext |
Appears in Collections: | EEE Journal Articles |
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TMM_revision_4k.pdf | 2.49 MB | Adobe PDF | View/Open |
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