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I4U Submission to NIST SRE 2018: Leveraging from a Decade of Shared Experiences., , , , , , , , , and 10 other author(s). INTERSPEECH, page 1497-1501. ISCA, (2019)The I4U Mega Fusion and Collaboration for NIST Speaker Recognition Evaluation 2016., , , , , , , , , and 52 other author(s). INTERSPEECH, page 1328-1332. ISCA, (2017)A bridge between features and evidence for binary attribute-driven perfect privacy., , , , and . CoRR, (2021)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)I4U System Description for NIST SRE'20 CTS Challenge., , , , , , , , , and 16 other author(s). CoRR, (2022)Un Sous-espace Thématique Latent pour la Compréhension du Langage Parlé (A Latent Topic-based Subspace for Spoken Language Understanding)., , , , , , and . JEP-TALN-RECITAL (1), page 651-659. AFCP - ATALA, (2016)On Robustness of Unsupervised Domain Adaptation for Speaker Recognition., and . INTERSPEECH, page 2958-2962. ISCA, (2019)Studying Squeeze-and-Excitation Used in CNN for Speaker Verification., and . ASRU, page 1110-1115. IEEE, (2021)Adaptation Strategy and Clustering from Scratch for New Domains of Speaker Recognition., and . Odyssey, page 81-87. ISCA, (2020)