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 [BibTeX] [Marc21]
Detection of disguised speech in forensic science by humans and automatic systems
Type of publication: Thesis
Citation: Pettinato_THESIS_2020
Year: 2020
Month: July
School: Université de Lausanne Ecole des Sciences Criminelles
Note: Master Thesis
Abstract: The step preceding the speaker identification process consists in the determination of the authenticity of a speech sample. The focus of this thesis is on the performance of humans in detecting altered samples from replay, speech synthesis (TTS) and voice conversion (VC) systems. A listening test was constructed on the online survey platform LimeSurvey. The participants were asked to assess a series of recordings by first giving a binary evaluation (“authentic” or “altered”) and then by specifying their level of confidence on a 5-point scale. Moreover, the logic behind the aural approach was studied by inspecting the criteria used by the respondents in the assessment of the recordings. The same samples were also evaluated with an automatic LFCC-GMM-based system, trained on two different datasets, in order to make a comparison. The results show that the human’s performance (EER=0.10) surpasses the machine’s (EER=0.35 and EER=0.46) in the detection of the altered samples. However, sophisticated voice disguise systems have now reached levels of quality that can also easily fool most humans, which makes them a real threat to security and the identification process.
Keywords: authentication, Biometrics, speaker recognition, Spoofing, Voice disguise
Projects Idiap
Authors Pettinato, Michela
Added by: [UNK]
Total mark: 0
  • Pettinato_THESIS_2020.pdf