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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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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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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-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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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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Learning emotions latent representation with CVAE for Text-Driven Expressive AudioVisual Speech Synthesis
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In: ISSN: 0893-6080 ; Neural Networks ; https://hal.inria.fr/hal-03204193 ; Neural Networks, Elsevier, 2021, 141, pp.315-329. ⟨10.1016/j.neunet.2021.04.021⟩ (2021)
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Using Silence MR Image to Synthesise Dynamic MRI Vocal Tract Data of CV
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In: INTERSPEECH 2020 ; https://hal.inria.fr/hal-03090808 ; INTERSPEECH 2020, Oct 2020, Shangaï / Virtual, China ; http://www.interspeech2020.org/ (2020)
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Audiovisual synthesis of expressive speech : modeling of emotions with deep learning ; Synthèse audiovisuelle de la parole expressive : modélisation des émotions par apprentissage profond
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In: https://hal.inria.fr/tel-03079349 ; Informatique [cs]. Université de Lorraine, 2020. Français. ⟨NNT : 2020LORR0137⟩ (2020)
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Introducing the VoicePrivacy initiative
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In: INTERSPEECH 2020 ; https://hal.inria.fr/hal-02562199 ; INTERSPEECH 2020, Oct 2020, Shanghai, China (2020)
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Duration modelling and evaluation for Arabic statistical parametric speech synthesis
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In: ISSN: 1380-7501 ; EISSN: 1573-7721 ; Multimedia Tools and Applications ; https://hal.inria.fr/hal-03007287 ; Multimedia Tools and Applications, Springer Verlag, 2020, ⟨10.1007/s11042-020-09901-7⟩ (2020)
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F0 modeling using DNN for Arabic parametric speech synthesis
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In: INNSBDDL 2019 - INNS Big Data and Deep Learning ; https://hal.inria.fr/hal-02177496 ; INNSBDDL 2019 - INNS Big Data and Deep Learning, Apr 2019, Sestri Levante, Italy (2019)
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Articulatory speech synthesis ; Synthèse articulatoire de la parole
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In: https://hal.archives-ouvertes.fr/tel-02433528 ; Computation and Language [cs.CL]. Université de Lorraine, 2019. English. ⟨NNT : 2019LORR0166⟩ (2019)
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Modeling Labial Coarticulation with Bidirectional Gated Recurrent Networks and Transfer Learning
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In: INTERSPEECH 2019 - 20th Annual Conference of the International Speech Communication Association ; https://hal.inria.fr/hal-02175780 ; INTERSPEECH 2019 - 20th Annual Conference of the International Speech Communication Association, Sep 2019, Graz, Austria (2019)
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Conditional Variational Auto-Encoder for Text-Driven Expressive AudioVisual Speech Synthesis
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In: INTERSPEECH 2019 - 20th Annual Conference of the International Speech Communication Association ; https://hal.inria.fr/hal-02175776 ; INTERSPEECH 2019 - 20th Annual Conference of the International Speech Communication Association, Sep 2019, Graz, Austria (2019)
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Evaluation of speech unit modelling for HMM-based speech synthesis for Arabic
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In: ISSN: 1381-2416 ; EISSN: 1572-8110 ; International Journal of Speech Technology ; https://hal.inria.fr/hal-01936963 ; International Journal of Speech Technology, Springer Verlag, 2018, pp.1-12. ⟨10.1007/s10772-018-09558-6⟩ (2018)
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DNN-Based Speech Synthesis for Arabic: Modelling and Evaluation
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In: SLSP 2018 - 6th International Conference on Statistical Language and Speech Processing ; https://hal.inria.fr/hal-01904512 ; SLSP 2018 - 6th International Conference on Statistical Language and Speech Processing, Oct 2018, Mons, Belgium (2018)
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Statistical modelling of speech units in HMM-based speech synthesis for Arabic
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In: LTC 2017 - 8th Language & Technology Conference ; https://hal.inria.fr/hal-01649034 ; LTC 2017 - 8th Language & Technology Conference, Nov 2017, Poznań, Poland. pp.1-5 (2017)
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