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Speaker Verification on VoxCeleb-E

0.27EERLoRA Adapter MFA
-2.719217.457937.63557.8121Oct 5, 2025Nov 20, 2025Jan 5, 2026Feb 20, 2026Apr 7, 2026May 23, 2026Jul 8, 2026

Evaluation results

MethodLinks
LoRA Adapter MFAFrontend=w2v-BERT 2.0, Params=580+6.2M, LMFT=true, Score calibration=true2025.100.270.028————
LoRA Adapter MFAFrontend=w2v-BERT 2.0, Params=580+6.2M, LMFT=true, Score calibration=false2025.100.310.032————
W2V-BERT 2.0Params=587M, GMACs=57.90, Large-Margin Finetuning=-, Training Data=VoxBlink2 + VoxCeleb22026.030.31—————
ResNet293Frontend=Fbank, Params=98.9M, LMFT=true, Score calibration=true2025.100.370.037————
LoRA Adapter MFAFrontend=w2v-BERT 2.0, Params=580+6.2M, LMFT=false, Score calibration=false2025.100.380.04————
ECAPA-TDNNScoring=Cosine scoring2026.030.45—————
SimAM-ResNet100Params=50.2M, GMACs=57.24, Large-Margin Finetuning=-, Training Data=VoxBlink2 + VoxCeleb22026.030.46—————
ECAPA-TDNN(C=512)Frontend=WavLM Large, Params=317+8.8M, LMFT=true, Score calibration=true2025.100.48—————
CA-MHFAFrontend=WavLM Large, Params=317+2.3M, LMFT=true, Score calibration=true2025.100.48—————
LAP+ASTPFrontend=WavLM Large, Params=317+2.3M, LMFT=true, Score calibration=true2025.100.50.055————
W2V-BERT 2.0Params=587M, GMACs=57.90, Large-Margin Finetuning=Yes, Training Data=VoxCeleb2-dev2026.030.51—————
ReDimNet2-B6Params=12.3M, GMACs=13.05, Large-Margin Finetuning=Yes, Training Data=VoxCeleb2-dev2026.030.52—————
ReDimNet-B6Frontend=Fbank, Params=15.0M, LMFT=true, Score calibration=true2025.100.530.051————
ReDimNet-B6Params=15.0M, GMACs=20.27, Large-Margin Finetuning=Yes, Training Data=VoxCeleb2-dev2026.030.55—————
ReDimNet2-B5Params=8.9M, GMACs=9.62, Large-Margin Finetuning=Yes, Training Data=VoxCeleb2-dev2026.030.56—————
ECAPA-TDNN(C=512)Frontend=UniSpeech-SAT Large, Params=317+8.8M, LMFT=true, Score calibration=true2025.100.57—————
ReDimNet2-B4Params=6.6M, GMACs=4.62, Large-Margin Finetuning=Yes, Training Data=VoxCeleb2-dev2026.030.58—————
ReDimNet-B5Params=9.2M, GMACs=9.87, Large-Margin Finetuning=Yes, Training Data=VoxCeleb2-dev2026.030.61—————
ECAPA2Params=27.1M, GMACs=187.0*, Large-Margin Finetuning=Yes, Training Data=VoxCeleb2-dev2026.030.62—————
SimAM-ResNet34Params=25.2M, GMACs=18.20, Large-Margin Finetuning=-, Training Data=VoxBlink2 + VoxCeleb22026.030.62—————
ECAPA-TDNN(C=512)Frontend=Wav2Wec2.0 Large, Params=317+8.8M, LMFT=true, Score calibration=true2025.100.63—————
WavLMParams=324M, GMACs=26.53, Large-Margin Finetuning=Yes, Training Data=VoxCeleb2-dev2026.030.63—————
ECAPA-TDNN(C=512)Frontend=HuBERT Large, Params=317+8.8M, LMFT=true, Score calibration=true2025.100.65—————
MFAFrontend=Nemo Large, Params=131M, LMFT=true, Score calibration=true2025.100.660.071————
ReDimNet2-B3Params=4.1M, GMACs=2.70, Large-Margin Finetuning=Yes, Training Data=VoxCeleb2-dev2026.030.66—————
ResNet221Frontend=Fbank, Params=23.8M, LMFT=true, Score calibration=true2025.100.68—————
ReDimNet-B4Params=6.3M, GMACs=4.80, Large-Margin Finetuning=Yes, Training Data=VoxCeleb2-dev2026.030.68—————
ResNet293Params=28.6M, GMACs=28.10, Large-Margin Finetuning=Yes, Training Data=VoxCeleb2-dev2026.030.71—————
ReDimNet-B3Params=3.0M, GMACs=3.00, Large-Margin Finetuning=Yes, Training Data=VoxCeleb2-dev2026.030.73—————
ERes2NetV2Frontend=Fbank, Params=17.8M, LMFT=true, Score calibration=false2025.100.760.082————
ReDimNet-B2Params=4.7M, GMACs=0.90, Large-Margin Finetuning=Yes, Training Data=VoxCeleb2-dev2026.030.76—————
ReDimNet2-B2Params=3.6M, GMACs=0.95, Large-Margin Finetuning=Yes, Training Data=VoxCeleb2-dev2026.030.76—————
SpeakerCard-1MRegime=audio only2026.060.79—————
CAM++Params=7.2M, GMACs=1.15, Large-Margin Finetuning=Yes, Training Data=VoxCeleb2-dev2026.030.85—————
TRKDTeacher Model=ReDim-B5, Student Model=ReDim-B22026.010.885—————
CAM++Frontend=Fbank, Params=7.2M, LMFT=false, Score calibration=false2025.100.890.1————
Gemini-DFResNet114Params=6.5M, GMACs=5.42, Large-Margin Finetuning=No, Training Data=VoxCeleb2-dev2026.030.91—————
SpeakerCard-1MRegime=balanced2026.060.91—————
WavLM-Base SV2026.060.92—————
CAM++# Param.=7.2 M, Uncertainty-aware cosine score=false2026.070.9310.109————
ReDimNet2-B1Params=2.1M, GMACs=0.56, Large-Margin Finetuning=Yes, Training Data=VoxCeleb2-dev2026.030.96—————
ECAPA512 + U^3-xi# Param.=6.69 M, Loss=UAAM-Softmax (1)+(4), Uncertainty-aware cosine score=true2026.070.9650.11———21.22
ECAPA512 + U^3-xi# Param.=6.69 M, Loss=USphereFace2 (1)+(4), Uncertainty-aware cosine score=true2026.070.9650.108———12.81
ReDimNet-B1Params=2.2M, GMACs=0.54, Large-Margin Finetuning=Yes, Training Data=VoxCeleb2-dev2026.030.97—————
ChebyAAMObjective=ChebyAAM, Backbone=ECAPA-TDNN2026.010.97930.1127————
ECAPA512 + U^3-xi# Param.=6.69 M, Loss=UAAM-Softmax (1)+(2), Uncertainty-aware cosine score=true2026.070.9880.113———18.53
ECAPA-TDNN2026.060.99—————
ECAPA512 + U^3-xi# Param.=6.69 M, Loss=UAM-Softmax (1)+(4), Uncertainty-aware cosine score=true2026.070.9910.109———19.46
AAM-SoftmaxObjective=AAM-Softmax, Backbone=ECAPA-TDNN2026.011.00660.1132————
SA-TinyLLaMAScoring=Log-likelihood based scoring2026.031.03—————
ECAPA512 + U^3-xi# Param.=6.69 M, Loss=UAAM-Softmax (1) [22], Uncertainty-aware cosine score=true2026.071.0350.115———14.95
ECAPA512 + U^3-xi# Param.=6.69 M, Loss=USphereFace2 (1)+(4), Uncertainty-aware cosine score=false2026.071.0350.119———5.21
NeXt-TDNN-l (C=256)Params=6.0M, GMACs=1.13*, Large-Margin Finetuning=No, Training Data=VoxCeleb2-dev2026.031.04—————
NeXt-TDNN (C=256)Params=7.1M, GMACs=1.35*, Large-Margin Finetuning=No, Training Data=VoxCeleb2-dev2026.031.04—————
ResNet34# Param.=6.63 M, Uncertainty-aware cosine score=false2026.071.0490.121————
ECAPA512 + U^3-xi# Param.=6.69 M, Loss=UAAM-Softmax (1)+(4), Uncertainty-aware cosine score=false2026.071.050.122———13.4
Teacher (w/o KD)Teacher Model=ECAPA1024, Student Model=ECAPA4002026.011.051—————
TRKDTeacher Model=RN152, Student Model=MNV22026.011.068—————
ECAPA512 + U^3-xi# Param.=6.69 M, Loss=UAAM-Softmax (1)+(2), Uncertainty-aware cosine score=false2026.071.0690.121———9.26
SpeakerCard-1MRegime=retrieval-spec.2026.061.07—————
Teachersource=Wespeaker2026.071.070.117————
ECAPA1024# Param.=14.65 M, Uncertainty-aware cosine score=false2026.071.0720.117————
ECAPA512 + U^3-xi# Param.=6.69 M, Loss=UAAM-Softmax (1) [22], Uncertainty-aware cosine score=false2026.071.0750.121———10.6
ECAPA512 + U^3-xi# Param.=6.69 M, Loss=UAM-Softmax (1)+(4), Uncertainty-aware cosine score=false2026.071.0760.119———11.46
AM-SoftmaxObjective=AM-Softmax, Backbone=ECAPA-TDNN2026.011.08720.1301————
ECAPA512 + U^3-xi# Param.=6.69 M, Loss=UAAM-Softmax (3), Uncertainty-aware cosine score=true2026.071.0940.125———9.05
ECAPA512 + U^3-xi# Param.=6.69 M, Loss=UAAM-Softmax (3), Uncertainty-aware cosine score=false2026.071.1020.127———8.32
TRKDTeacher Model=ECAPA1024, Student Model=ECAPA4002026.011.115—————
ECAPA-TDNN(C=1024)Frontend=Fbank, Params=14.7M, LMFT=false, Score calibration=false2025.101.120.132————
ECAPA512# Param.=6.19 M, Loss=SphereFace2 [37], [38], Uncertainty-aware cosine score=false2026.071.1210.125————
Gemini SD-ResNet38# Param.=6.72 M, Uncertainty-aware cosine score=false2026.071.130.117————
TRKDTeacher Model=SAM-RN50, Student Model=R2N342026.011.157—————
ReDimNet2-B0Params=1.1M, GMACs=0.33, Large-Margin Finetuning=Yes, Training Data=VoxCeleb2-dev2026.031.16—————
NeXt-TDNN (C=128)Params=1.9M, GMACs=0.35*, Large-Margin Finetuning=No, Training Data=VoxCeleb2-dev2026.031.17—————
CFKDBitrate=24 kbps, Backbone=ECAPA-TDNN1024, lambda=402026.071.20.139————
ECAPA512# Param.=6.19 M, Loss=AM-Softmax [35], [36], Uncertainty-aware cosine score=false2026.071.2060.133————
ECAPA512# Param.=6.19 M, Loss=AAM-Softmax [30], Uncertainty-aware cosine score=false2026.071.2090.136————
ECAPA (C=512)Params=6.2M, GMACs=1.04, Large-Margin Finetuning=No, Training Data=VoxCeleb2-dev2026.031.21—————
NeXt-TDNN-l (C=128)Params=1.6M, GMACs=0.29*, Large-Margin Finetuning=No, Training Data=VoxCeleb2-dev2026.031.24—————
ReDimNet-B0Params=1.0M, GMACs=0.43, Large-Margin Finetuning=Yes, Training Data=VoxCeleb2-dev2026.031.25—————
CFKDBitrate=12 kbps, Backbone=ECAPA-TDNN1024, lambda=402026.071.30.15————
TRKDTeacher Model=RN34, Student Model=RN182026.011.322—————
Student (w/o KD)Teacher Model=ECAPA1024, Student Model=ECAPA4002026.011.395—————
A-SoftmaxObjective=A-Softmax, Backbone=ECAPA-TDNN2026.011.4290.175————
TRKDTeacher Model=CAM++, Student Model=X-vector2026.011.692—————
CFKDBitrate=6 kbps, Backbone=ECAPA-TDNN1024, lambda=402026.071.80.208————
SA-TinyLLaMAScoring=Log-likelihood based scoring, Variant=XS2026.032.21—————
CFKDBitrate=3 kbps, Backbone=ECAPA-TDNN1024, lambda=402026.073.470.386————
SA-TinyLLaMAScoring=Log-likelihood based scoring, Backbone=Frozen2026.034.21—————
CFKDBitrate=1.5 kbps, Backbone=ECAPA-TDNN1024, lambda=402026.079.720.787————
SA-Ministral3Scoring=Log-likelihood based scoring2026.0315.88—————
SA-TinyLLaMAScoring=Log-likelihood based scoring, Backbone=Frozen, Variant=XS2026.0327.82—————
KiwanoBackbone Architecture=fwSE-ResNet-2002026.0664—————
WeSpeakerBackbone Architecture=ResNet-2932026.0671—————
3D-SpeakerBackbone Architecture=ERes2Net-large-lm2026.0675—————
D-ALMFTEncoder=ResNet342026.01——1.182.154.06—
D-ALMFTEncoder=ECAPA-TDNN2026.01——1.182.314.17—
D-ALMFTEncoder=ERes2NetV22026.01——1.142.163.89—
DAME-FT-HWEncoder=ResNet342026.01——0.972.114.03—
DAME-FT-HWEncoder=ECAPA-TDNN2026.01——1.142.34.22—