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Deep Neural Networks and Hidden Markov Models in i-vector-based Text-Dependent Speaker Verification.

, , , , and . Odyssey, page 24-30. ISCA, (2016)

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Discriminatively Re-trained i-vector Extractor for Speaker Recognition., , , , and . CoRR, (2018)GMM Weights Adaptation Based on Subspace Approaches for Speaker Verification., , , , , and . Odyssey, ISCA, (2014)BAT System Description for NIST LRE 2015., , , , , , , , and . Odyssey, page 166-173. ISCA, (2016)Analysis and Optimization of Bottleneck Features for Speaker Recognition., , , , , , , and . Odyssey, page 352-357. ISCA, (2016)Data selection and calibration issues in automatic language recognition - investigation with BUT-AGNITIO NIST LRE 2009 system., , , , , , , , , and 1 other author(s). Odyssey, page 37. ISCA, (2010)An Attention-Based Backend Allowing Efficient Fine-Tuning of Transformer Models for Speaker Verification., , , , , and . SLT, page 555-562. IEEE, (2022)Automatic language identification using deep neural networks., , , , , and . ICASSP, page 5337-5341. IEEE, (2014)Domain adaptation via within-class covariance correction in I-vector based speaker recognition systems., , , , , , and . ICASSP, page 4032-4036. IEEE, (2014)End-to-End DNN Based Speaker Recognition Inspired by I-Vector and PLDA., , , , , and . ICASSP, page 4874-4878. IEEE, (2018)Analysis of BUT-PT Submission for NIST LRE 2017., , , , , , , , , and 5 other author(s). Odyssey, page 47-53. ISCA, (2018)