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Utterance partitioning for speaker recognition: an experimental review and analysis with new findings under GMM-SVM framework
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In: ISSN: 1381-2416 ; EISSN: 1572-8110 ; International Journal of Speech Technology ; https://hal.archives-ouvertes.fr/hal-03232723 ; International Journal of Speech Technology, Springer Verlag, In press, ⟨10.1007/s10772-021-09862-8⟩ (2021)
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Speaker Attentive Speech Emotion Recognition
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In: Proccedings of interspeech 2021 ; Interspeech 2021 ; https://hal.archives-ouvertes.fr/hal-03554368 ; Interspeech 2021, Aug 2021, Brno, Czech Republic. pp.2866-2870, ⟨10.21437/interspeech.2021-573⟩ (2021)
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Privacy and utility of x-vector based speaker anonymization
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In: https://hal.inria.fr/hal-03197376 ; 2021 (2021)
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Supplementary material to the paper The VoicePrivacy 2020 Challenge: Results and findings
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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
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In: https://hal.archives-ouvertes.fr/hal-03335126 ; 2021 (2021)
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The VoicePrivacy 2020 Challenge: Results and findings
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In: https://hal.archives-ouvertes.fr/hal-03332224 ; 2021 (2021)
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Supplementary material to the paper The VoicePrivacy 2020 Challenge: Results and findings
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In: https://hal.archives-ouvertes.fr/hal-03335126 ; 2021 (2021)
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The VoicePrivacy 2020 Challenge: Results and findings
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In: https://hal.archives-ouvertes.fr/hal-03332224 ; 2021 (2021)
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Enhancing Speech Privacy with Slicing
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In: https://hal.inria.fr/hal-03369137 ; 2021 (2021)
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Supplementary material to the paper The VoicePrivacy 2020 Challenge: Results and findings
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Tomashenko, Natalia; Wang, Xin; Vincent, Emmanuel; Patino, Jose; Srivastava, Brij Mohan Lal; Noé, Paul-Gauthier; Nautsch, Andreas; Evans, Nicholas; Yamagishi, Junichi; O'brien, Benjamin; Chanclu, Anaïs; Bonastre, Jean-François; Todisco, Massimiliano; Maouche, Mohamed
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In: https://hal.archives-ouvertes.fr/hal-03335126 ; 2021 (2021)
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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.
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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
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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
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In: https://hal.archives-ouvertes.fr/hal-03335126 ; 2021 (2021)
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The VoicePrivacy 2020 Challenge: Results and findings
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In: https://hal.archives-ouvertes.fr/hal-03332224 ; 2021 (2021)
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Privacy and utility of x-vector based speaker anonymization
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In: https://hal.inria.fr/hal-03197376 ; 2021 (2021)
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Kurdish spoken dialect recognition using x-vector speaker embeddings
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In: https://hal.archives-ouvertes.fr/hal-03262435 ; 2021 (2021)
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Evaluation of Speaker Anonymization on Emotional Speech
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In: 1st ISCA Symposium on Security and Privacy in Speech Communication ; https://hal.inria.fr/hal-03377797 ; 1st ISCA Symposium on Security and Privacy in Speech Communication, Nov 2021, Virtual, Germany (2021)
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An investigation into variability conditions in the SRE 2004 and 2008 Corpora ...
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Разработка современной системы распознавания русскоязычной телефонной речи ... : Speech recognition system for russian-language telephone speech ...
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U-Vectors: Generating Clusterable Speaker Embedding from Unlabeled Data
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In: Applied Sciences ; Volume 11 ; Issue 21 (2021)
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