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1
Supplementary material to the paper The VoicePrivacy 2020 Challenge: Results and findings
In: https://hal.archives-ouvertes.fr/hal-03335126 ; 2021 (2021)
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Supplementary material to the paper The VoicePrivacy 2020 Challenge: Results and findings
In: https://hal.archives-ouvertes.fr/hal-03335126 ; 2021 (2021)
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3
The VoicePrivacy 2020 Challenge: Results and findings
In: https://hal.archives-ouvertes.fr/hal-03332224 ; 2021 (2021)
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4
Supplementary material to the paper The VoicePrivacy 2020 Challenge: Results and findings
In: https://hal.archives-ouvertes.fr/hal-03335126 ; 2021 (2021)
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5
The VoicePrivacy 2020 Challenge: Results and findings
In: https://hal.archives-ouvertes.fr/hal-03332224 ; 2021 (2021)
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6
Supplementary material to the paper The VoicePrivacy 2020 Challenge: Results and findings
In: https://hal.archives-ouvertes.fr/hal-03335126 ; 2021 (2021)
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7
Supplementary material to the paper The VoicePrivacy 2020 Challenge: Results and findings
In: https://hal.archives-ouvertes.fr/hal-03335126 ; 2021 (2021)
Abstract: Supplementary material to the paper "The VoicePrivacy 2020 Challenge: Results and findings" (https://hal.archives-ouvertes.fr/hal-03332224) submitted to CSL. ; The VoicePrivacy 2020 Challenge focuses on developing anonymization solutions for speech technology. This report complements the summary results and analyses presented by Tomashenko et al. (2021). After quickly recalling the challenge design and the submitted anonymization systems, we provide more detailed results and analyses. First, we present objective evaluation results for the primary challenge metrics and for alternative metrics and attack models, and we compare them with each other. Second, we present subjective evaluation results for speaker verifiability, speech naturalness, and speech intelligibility. Finally, we compare these objective and subjective evaluation results with each other.
Keyword: [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]; anonymization; attack model; automatic speech recognition; metrics; privacy; speaker verification; speech synthesis; utility; voice conversion
URL: https://hal.archives-ouvertes.fr/hal-03335126v2/file/VoicePrivacyCSL_paper_suppl_hal3.pdf
https://hal.archives-ouvertes.fr/hal-03335126v2/document
https://hal.archives-ouvertes.fr/hal-03335126
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8
The VoicePrivacy 2020 Challenge: Results and findings
In: https://hal.archives-ouvertes.fr/hal-03332224 ; 2021 (2021)
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9
Discriminating speakers using perceptual clustering interface
In: XVII AISV Conference: Speaker Individuality in Phonetics and Speech Sciences: Speech Technology and Forensic Applications ; https://hal.archives-ouvertes.fr/hal-03160943 ; XVII AISV Conference: Speaker Individuality in Phonetics and Speech Sciences: Speech Technology and Forensic Applications, Feb 2021, Zurich, Switzerland (2021)
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10
Anonymous speaker clusters: Making distinctions between anonymised speech recordings with clustering interface
In: INTERSPEECH 2021 ; https://hal.archives-ouvertes.fr/hal-03267084 ; INTERSPEECH 2021, Aug 2021, Brno, Czech Republic (2021)
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11
Presentation matters: Evaluating speaker identification tasks
In: INTERSPEECH 2021 ; https://hal.archives-ouvertes.fr/hal-03267089 ; INTERSPEECH 2021, Aug 2021, Brno, Czech Republic (2021)
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Anonymous speaker clusters: Making distinctions between anonymised speech recordings with clustering interface
In: INTERSPEECH 2021 ; https://hal.archives-ouvertes.fr/hal-03267084 ; INTERSPEECH 2021, Aug 2021, Brno, Czech Republic (2021)
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