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Speaker Verification on VoxCeleb1 hard (test)

1.857EERRecXi
1.638083.115794.59356.07121Jun 18, 2019Mar 5, 2020Nov 21, 2020Aug 9, 2021Apr 27, 2022Jan 13, 2023Oct 2, 2023

Evaluation results

MethodLinks
RecXiAugmentation=true, Parameters (M)=7.06, system_id=#92023.101.857——0.179
Xi + tResNet (baseline)Augmentation=true, Parameters (M)=6.54, system_id=#82023.101.942——0.186
MFA-TDNN (standard)Augmentation=true, Parameters (M)=7.322023.102.049——0.19
RecXiAugmentation=false, Parameters (M)=7.06, system_id=#52023.102.097——0.196
Xi + tResNet (baseline)Augmentation=false, Parameters (M)=6.54, system_id=#42023.102.169——0.202
MFA-TDNN (lite)Augmentation=true, Parameters (M)=5.932023.102.174——0.199
UP-LS UP-PLDA2023.102.18——0.224
H/ASP (AP+softmax)Augmentation=true, Parameters (M)=8.02023.102.21———
ResNet34 (re-implemented)Augmentation=true, Parameters (M)=6.63, system_id=#72023.102.221——0.208
ECAPA-TDNN (re-implemented)Augmentation=true, Parameters (M)=6.19, system_id=#62023.102.249——0.223
TSP + tResNet (baseline)Augmentation=false, Parameters (M)=6.21, system_id=#32023.102.257——0.204
ECAPA-TDNN (MBFA-MW)Augmentation=true2023.102.31——0.222
ECAPA-TDNNAugmentation=true, Parameters (M)=6.22023.102.32——0.218
H/ASP (AAM-softmax)Augmentation=true, Parameters (M)=8.02023.102.49———
SI-Net50Augmentation=false2023.102.5———
ResNet34 (re-implemented)Augmentation=false, Parameters (M)=6.63, system_id=#22023.102.5——0.224
RSKNet-MTSPAugmentation=false, Parameters (M)=13.92023.102.52——0.237
ECAPA-TDNN (re-implemented)Augmentation=false, Parameters (M)=6.19, system_id=#12023.102.674——0.235
Res2Net-26w8sAugmentation=true, Parameters (M)=9.32023.102.72——0.272
ResNet34-SKDFEAugmentation=false, Parameters (M)=5.982023.102.76——0.278
H/ASP (AP+softmax)Augmentation=false, Parameters (M)=8.02023.102.77———
H/ASP (AAM-softmax)Augmentation=false, Parameters (M)=8.02023.102.78———
AAM-softmax (x-vector)Model=TDNN (x-vector), Loss=AAM-softmax, Training set=VoxCeleb22019.064.732———
Xie et al.Model=Thin ResNet-34, Loss=Softmax, Training set=VoxCeleb22019.065.06———
Chung et al.Model=ResNet-50, Loss=Softmax + Contrastive, Training set=VoxCeleb22019.067.33———
ECAPA-TDNNinput=40-dimensional filterbanks, loss=AAM softmax2021.09—3.10.05—
w2v2-aampooling=mean&std, loss=AAM softmax, feature encoder=frozen2021.09—4.330.08—
w2v2-bcescoring=computes scores directly, feature encoder=frozen2021.09—11.340.83—
w2v2-cepooling=mean&std, feature encoder=frozen2021.09—4.910.13—
x-vectorinput=40-dimensional filterbanks2021.09—8.750.05—