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Effect of multi-condition training and speech enhancement methods on spoofing detection.

, , , , , and . SPLINE, page 1-5. IEEE, (2016)

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UIAI System for Short-Duration Speaker Verification Challenge 2020., , , , , , , and . CoRR, (2020)Improving Speaker Verification Performance in Presence of Spoofing Attacks Using Out-of-Domain Spoofed Data., , , and . INTERSPEECH, page 2611-2615. ISCA, (2017)Fast computation of speaker characterization vector using MLLR and sufficient statistics in anchor model framework., and . INTERSPEECH, page 2738-2741. ISCA, (2010)Anchor and UBM-based multi-class MLLR m-vector system for speaker verification., and . INTERSPEECH, page 2450-2454. ISCA, (2013)Text-independent speaker identification using vocal tract length normalization for building universal background model., , and . INTERSPEECH, page 2331-2334. ISCA, (2009)Eigen-Voice Based Anchor Modeling System for Speaker Identification Using MLLR Super-Vector., and . INTERSPEECH, page 2357-2360. ISCA, (2011)Incorporating Pass-Phrase Dependent Background Models for Text Dependent Speaker Verification., and . CoRR, (2016)Data augmentation enhanced speaker enrollment for text-dependent speaker verification., , , and . CoRR, (2020)Time-Contrastive Learning Based Deep Bottleneck Features for Text-Dependent Speaker Verification., , , , and . IEEE ACM Trans. Audio Speech Lang. Process., 27 (8): 1267-1279 (2019)Application of Artificial Intelligence on Post Pandemic Situation and Lesson Learn for Future Prospects., , , , and . J. Exp. Theor. Artif. Intell., 35 (3): 327-344 (April 2023)