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RETRIEVING SPEAKER INFORMATION FROM PERSONALIZED ACOUSTIC MODELS FOR SPEECH RECOGNITION
In: IEEE ICASSP 2022 ; https://hal.archives-ouvertes.fr/hal-03539741 ; IEEE ICASSP 2022, 2022, Singapour, Singapore (2022)
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2
The VoicePrivacy 2022 Challenge Evaluation Plan ...
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Automatic Classification of Phonation Types in Spontaneous Speech: Towards a New Workflow for the Characterization of Speakers’ Voice Quality
In: Interspeech 2021 ; https://hal.archives-ouvertes.fr/hal-03334492 ; Interspeech 2021, Aug 2021, Brno, Czech Republic. pp.1015-1018, ⟨10.21437/Interspeech.2021-1765⟩ (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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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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6
The VoicePrivacy 2020 Challenge: Results and findings
In: https://hal.archives-ouvertes.fr/hal-03332224 ; 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)
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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
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-03335126v3/document
https://hal.archives-ouvertes.fr/hal-03335126v3/file/VoicePrivacyCSL_paper_report_hal2_.pdf
https://hal.archives-ouvertes.fr/hal-03335126
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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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11
The VoicePrivacy 2020 Challenge: Results and findings
In: https://hal.archives-ouvertes.fr/hal-03332224 ; 2021 (2021)
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12
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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13
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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14
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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15
Introducing the VoicePrivacy initiative
In: INTERSPEECH 2020 ; https://hal.inria.fr/hal-02562199 ; INTERSPEECH 2020, Oct 2020, Shanghai, China (2020)
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16
The VoicePrivacy 2020 Challenge Evaluation Plan
In: https://hal.archives-ouvertes.fr/hal-03623450 ; [Other] LIA - Laboratoire Informatique d'Avignon; MULTISPEECH - Speech Modeling for Facilitating Oral-Based Communication Inria Nancy - Grand Est, LORIA - NLPKD - Department of Natural Language Processing & Knowledge Discovery; Eurecom [Sophia Antipolis]; University of Edinburgh. 2020 (2020)
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17
Speech Pseudonymisation Assessment Using Voice Similarity Matrices ...
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18
Automatic transcription of Somali language
Nocera, Pascal; Bonastre, Jean-François; Nimaan Abdillahi. - : Institut des Sciences et des Nouvelles Technologies - Centre d'Etudes et des Recherches de Djibouti, 2014
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19
A Tutorial on Text-Independent Speaker Verification
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20
Speaker verification by inexperienced and experienced listeners vs. speaker verification system
In: IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) ; https://hal.archives-ouvertes.fr/hal-01317620 ; IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), May 2011, Prague, Czech Republic. ⟨10.1109/ICASSP.2011.5947707⟩ (2011)
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