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An Overview of Indian Spoken Language Recognition from Machine Learning Perspective
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In: ISSN: 2375-4699 ; EISSN: 2375-4702 ; ACM Transactions on Asian and Low-Resource Language Information Processing ; https://hal.inria.fr/hal-03616853 ; ACM Transactions on Asian and Low-Resource Language Information Processing, ACM, In press, ⟨10.1145/3523179⟩ (2022)
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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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Benchmarking and challenges in security and privacy for voice biometrics
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Bonastre, Jean-Francois; Delgado, Hector; Evans, Nicholas; Kinnunen, Tomi; Lee, Kong Aik; Liu, Xuechen; Nautsch, Andreas; Noe, Paul-Gauthier; Patino, Jose; Sahidullah, Md; Srivastava, Brij Mohan Lal; Todisco, Massimiliano; Tomashenko, Natalia; Vincent, Emmanuel; Wang, Xin; Yamagishi, Junichi
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In: SPSC 2021, 1st ISCA Symposium on Security and Privacy in Speech Communication ; https://hal.archives-ouvertes.fr/hal-03346196 ; SPSC 2021, 1st ISCA Symposium on Security and Privacy in Speech Communication, ISCA, Nov 2021, Magdeburg, Germany. ⟨10.21437/SPSC.2021-11⟩ ; https://spsc-symposium2021.de/#home (2021)
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Abstract:
2021 ISCA Symposium on Security and Privacy in Speech Communication ; International audience ; For many decades, research in speech technologies has focused upon improving reliability. With this now meeting user expectations for a range of diverse applications, speech technology is today omni-present. As result, a focus on security and privacy has now come to the fore. Here, the research effort is in its relative infancy and progress calls for greater, multidisciplinary collaboration with security, privacy, legal and ethical experts among others. Such collaboration is now underway. To help catalyse the efforts, this paper provides a high-level overview of some related research. It targets the non-speech audience and describes the benchmarking methodology that has spearheaded progress in traditional research and which now drives recent security and privacy initiatives related to voice biometrics. We describe: the ASVspoof challenge relating to the development of spoofing countermeasures; the VoicePrivacy initiative which promotes research in anonymisation for privacy preservation.
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Keyword:
[INFO.INFO-IA]Computer Science [cs]/Computer Aided Engineering; SPSC
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URL: https://hal.archives-ouvertes.fr/hal-03346196 https://doi.org/10.21437/SPSC.2021-11
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Language recognition on unknown conditions: the LORIA-Inria-MULTISPEECH system for AP20-OLR Challenge
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In: https://hal.archives-ouvertes.fr/hal-03228823 ; 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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Evaluating Voice Conversion-based Privacy Protection against Informed Attackers
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In: ICASSP 2020 - 45th International Conference on Acoustics, Speech, and Signal Processing ; https://hal.inria.fr/hal-02355115 ; ICASSP 2020 - 45th International Conference on Acoustics, Speech, and Signal Processing, IEEE Signal Processing Society, May 2020, Barcelona, Spain. pp.2802-2806 (2020)
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