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Jeffreys Divergence-Based Regularization of Neural Network Output Distribution Applied to Speaker Recognition.

, and . ICASSP, page 1-5. IEEE, (2023)

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Jeffreys Divergence-Based Regularization of Neural Network Output Distribution Applied to Speaker Recognition., and . ICASSP, page 1-5. IEEE, (2023)Review of different robust x-vector extractors for speaker verification., , and . EUSIPCO, page 1-5. IEEE, (2020)The I4U Mega Fusion and Collaboration for NIST Speaker Recognition Evaluation 2016., , , , , , , , , and 52 other author(s). INTERSPEECH, page 1328-1332. ISCA, (2017)I4U Submission to NIST SRE 2018: Leveraging from a Decade of Shared Experiences., , , , , , , , , and 10 other author(s). INTERSPEECH, page 1497-1501. ISCA, (2019)Latent Topic-based Subspace for Natural Language Processing., , , and . J. Signal Process. Syst., 91 (8): 833-853 (2019)I4U Submission to NIST SRE 2018: Leveraging from a Decade of Shared Experiences., , , , , , , , , and 36 other author(s). CoRR, (2019)Exploring some limits of Gaussian PLDA modeling for i-vector distributions., , and . Odyssey, page 41-47. ISCA, (2014)A Bridge between Features and Evidence for Binary Attribute-Driven Perfect Privacy., , , , and . ICASSP, page 3094-3098. IEEE, (2022)Analyse en Composante Principale pour l'extraction des i-vecteurs en vérification du locuteur (Principal Component Analysis for i-vector extraction in speaker verification.) in French., , , and . JEP-TALN-RECITAL 2012, page 297-304. ATALA/AFCP, (2012)Studying Squeeze-and-Excitation Used in CNN for Speaker Verification., and . ASRU, page 1110-1115. IEEE, (2021)