A competition system submission that fuses MFCC i-vectors, DNN tandem i-vectors, TDNN x-vectors, and ResNet embeddings with variability compensation and domain adaptation, reporting detection costs of 0.392 on CMN2 and 0.494 on VAST.
V arious kinds of state-of-the-art speaker embedding extractors are explored
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The DKU-SMIIP System for NIST 2018 Speaker Recognition Evaluation
A competition system submission that fuses MFCC i-vectors, DNN tandem i-vectors, TDNN x-vectors, and ResNet embeddings with variability compensation and domain adaptation, reporting detection costs of 0.392 on CMN2 and 0.494 on VAST.