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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 9 of 9 1 An Overview of Indian Spoken Language Recognition from Machine Learning Perspective Dey, Spandan; Sahidullah, Md; Saha, Goutam 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) BASE Show details 2 Utterance partitioning for speaker recognition: an experimental review and analysis with new findings under GMM-SVM framework Sen, Nirmalya; Sahidullah, Md; Patil, Hemant... 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) BASE Show details 3 Privacy and utility of x-vector based speaker anonymization Srivastava, Brij Mohan Lal; Maouche, Mohamed; Sahidullah, Md... In: https://hal.inria.fr/hal-03197376 ; 2021 (2021) BASE Show details 4 Benchmarking and challenges in security and privacy for voice biometrics Bonastre, Jean-Francois; Delgado, Hector; Evans, Nicholas... 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) BASE Show details 5 Language recognition on unknown conditions: the LORIA-Inria-MULTISPEECH system for AP20-OLR Challenge Duroselle, Raphaël; Sahidullah, Md; Jouvet, Denis... In: Interspeech ; https://hal.archives-ouvertes.fr/hal-03228823 ; Interspeech, Aug 2021, Brno, Czech Republic (2021) BASE Show details 6 Language recognition on unknown conditions: the LORIA-Inria-MULTISPEECH system for AP20-OLR Challenge Duroselle, Raphaël; Sahidullah, Md; Jouvet, Denis... In: https://hal.archives-ouvertes.fr/hal-03228823 ; 2021 (2021) BASE Show details 7 Privacy and utility of x-vector based speaker anonymization Srivastava, Brij Mohan Lal; Maouche, Mohamed; Sahidullah, Md... In: https://hal.inria.fr/hal-03197376 ; 2021 (2021) BASE Show details 8 Evaluating Voice Conversion-based Privacy Protection against Informed Attackers Srivastava, Brij Mohan Lal; Vauquier, Nathalie; Sahidullah, Md; Bellet, Aurélien; Tommasi, Marc; Vincent, Emmanuel 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) Abstract: International audience ; Speech data conveys sensitive speaker attributes like identity or accent. With a small amount of found data, such attributes can be inferred and exploited for malicious purposes: voice cloning, spoofing, etc. Anonymization aims to make the data unlinkable, i.e., ensure that no utterance can be linked to its original speaker. In this paper, we investigate anonymization methods based on voice conversion. In contrast to prior work, we argue that various linkage attacks can be designed depending on the attackers' knowledge about the anonymization scheme. We compare two frequency warping-based conversion methods and a deep learning based method in three attack scenarios. The utility of converted speech is measured via the word error rate achieved by automatic speech recognition, while privacy protection is assessed by the increase in equal error rate achieved by state-of-the-art i-vector or x-vector based speaker verification. Our results show that voice conversion schemes are unable to effectively protect against an attacker that has extensive knowledge of the type of conversion and how it has been applied, but may provide some protection against less knowledgeable attackers. Keyword: [INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL]; [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG]; attacker; linkage attack; privacy; speaker verification; speech recognition; voice conversion URL: https://hal.inria.fr/hal-02355115v2/document https://hal.inria.fr/hal-02355115 https://hal.inria.fr/hal-02355115v2/file/ppvc_final.pdf BASE Hide details 9 Design, analysis and experimental evaluation of block based transformation in MFCC computation for speaker recognition Saha, Goutam; Sahidullah, Md. In: Speech communication. - Amsterdam [u.a.] : Elsevier 54 (2012) 4, 543-565 BLLDB OLC Linguistik Show details

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