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DF-ResNet: Boosting Speaker Verification Performance with Depth-First Design
Interspeech 2022
On the Importance of Different Frequency Bins for Speaker Verification
Self-Knowledge Distillation via Feature Enhancement for Speaker Verification
Non-Parallel Any-to-Many Voice Conversion by Replacing Speaker Statistics
We introduce the speaker modeling method (statistics based) into the voice conversion
Speaker Embedding Augmentation with Noise Distribution Matching.
Revisiting the Statistics Pooling Layer in Deep Speaker Embedding Learning
SELF-SUPERVISED LEARNING BASED DOMAIN ADAPTATION FOR ROBUST SPEAKER VERIFICATION
SYNAUG:SYNTHESIS-BASED DATA AUGMENTATION FOR TEXT-DEPENDENT SPEAKER VERIFICATION
Unit Selection Synthesis based Data Augmentation for Fixed Phrase Speaker Verification
Dual-adversarial domain adaptation for generalized replay attack detection
INTERSPEECH 2020
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