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Setup: fbank80, num_frms200, epoch150, ArcMargin, aug_prob0.6, speed_perturb (no spec_aug)
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Scoring: cosine (sub mean of vox2_dev), AS-Norm, QMF
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Test_trial: CNC-Eval-Avg.lst
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🔥 UPDATE 2022.07.12: We update this recipe according to the setups in the winning system of CNSRC 2022, and get obvious performance improvement compared with the old recipe. Check the commit1, commit2 for details.
- LR scheduler warmup from 0
- Remove one embedding layer
- Add large margin fine-tuning strategy (LM)
| Model | Params | FLOPs | LM | AS-Norm | QMF | EER (%) | minDCF (p=0.01) |
|---|---|---|---|---|---|---|---|
| ResNet34-TSTP-emb256 (OLD) | 6.70M | 4.55 G | × | × | × | 8.426 | 0.487 |
| ResNet34-TSTP-emb256 | 6.63M | 4.55 G | × | × | × | 7.134 | 0.408 |
| × | √ | × | 6.747 | 0.367 | |||
| × | √ | √ | 6.336 | 0.374 | |||
| √ | × | × | 6.652 | 0.393 | |||
| √ | √ | × | 6.492 | 0.354 | |||
| √ | √ | √ | 6.119 | 0.361 | |||
| ResNet221-TSTP-emb256 | 23.86M | 21.29 G | × | × | × | 5.965 | 0.362 |
| × | √ | × | 5.708 | 0.326 | |||
| √ | × | × | 5.886 | 0.362 | |||
| √ | √ | × | 5.655 | 0.330 | |||
| ECAPA_TDNN_GLOB_c512-ASTP-emb192 | 6.19M | 1.04 G | × | × | × | 8.313 | 0.432 |
| × | √ | × | 7.644 | 0.390 | |||
| √ | × | × | 8.004 | 0.422 | |||
| √ | √ | × | 7.417 | 0.379 | |||
| ECAPA_TDNN_GLOB_c1024-ASTP-emb192 | 14.65M | 2.65 G | × | × | × | 7.879 | 0.420 |
| × | √ | × | 7.412 | 0.379 | |||
| √ | × | × | 7.986 | 0.417 | |||
| √ | √ | × | 7.395 | 0.372 | |||
| RepVGG_TINY_A0 | 6.26M | 4.65 G | × | × | × | 6.883 | 0.399 |
| × | √ | × | 6.550 | 0.355 |