Speaker Identification on LibriSpeech (test)
99.25Top-1 AccuracyTARNet
Evaluation results
| Method | Links | ||||||
|---|---|---|---|---|---|---|---|
| TARNet2026.05 | 99.25 | — | 99.74 | 99.48 | 99.24 | 99.36 | |
| ECAPA-TDNN2026.05 | 97.8 | — | 99.68 | 97.59 | 97.8 | 97.69 | |
| DLSI-SM-VGG-M2026.05 | 97.52 | — | 99.62 | 97.27 | 97.52 | 97.39 | |
| Thin ResNet-342026.05 | 97.36 | — | 99.58 | 97.48 | 97.36 | 97.42 | |
| ResNeXt2026.05 | 97.24 | — | 99.45 | 97.1 | 97.24 | 97.17 | |
| VGG-CNN2026.05 | 97.1 | — | 99.51 | 97.36 | 97.1 | 97.23 | |
| DCSA-ResNet182026.05 | 96.4 | — | 99.65 | 96.19 | 96.39 | 96.29 | |
| LF-DNN-GCC2026.05 | 93.84 | — | 98.49 | 94.02 | 93.83 | 93.92 | |
| VGG-M-402026.05 | 93.38 | — | 98.38 | 93.51 | 93.36 | 93.43 | |
| x-vector2026.05 | 93.23 | — | 98.42 | 93.39 | 93.22 | 93.3 | |
| VGG-M2026.05 | 92.99 | — | 98.47 | 92.8 | 92.98 | 92.89 | |
| ResNetSE-34L2026.05 | 91.56 | — | 98.4 | 91.28 | 91.55 | 91.41 | |
| CNN-no-norm2026.05 | 90.33 | — | 98.03 | 90.54 | 90.32 | 90.43 | |
| CBOWEvaluation Protocol=Linear Classifier2020.10 | — | 99 | — | — | — | — | |
| COLAEvaluation Protocol=Linear Classifier2020.10 | — | 100 | — | — | — | — | |
| SGEvaluation Protocol=Linear Classifier2020.10 | — | 100 | — | — | — | — | |
| TemporalGapEvaluation Protocol=Linear Classifier2020.10 | — | 97 | — | — | — | — | |
| Triplet LossEvaluation Protocol=Linear Classifier2020.10 | — | 100 | — | — | — | — |