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merged 3 commits into from
Apr 7, 2022
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[vec]update the speaker verification model #1663

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d064c81
update the speaker verification model, test=doc
LeoMax-Xiong Apr 7, 2022
2a095db
remove unuse content in readme, test=doc
LeoMax-Xiong Apr 7, 2022
85e4e70
remove score content, test=doc
LeoMax-Xiong Apr 7, 2022
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164 changes: 83 additions & 81 deletions demos/speaker_verification/README.md
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Original file line number Diff line number Diff line change
Expand Up @@ -38,6 +38,7 @@ wget -c https://paddlespeech.bj.bcebos.com/vector/audio/85236145389.wav
```
Arguments:
- `input`(required): Audio file to recognize.
- `task` (required): Specify `vector` task. Default `spk`。
- `model`: Model type of vector task. Default: `ecapatdnn_voxceleb12`.
- `sample_rate`: Sample rate of the model. Default: `16000`.
- `config`: Config of vector task. Use pretrained model when it is None. Default: `None`.
Expand All @@ -47,45 +48,45 @@ wget -c https://paddlespeech.bj.bcebos.com/vector/audio/85236145389.wav
Output:

```bash
demo [ -5.749211 9.505463 -8.200284 -5.2075014 5.3940268
-3.04878 1.611095 10.127234 -10.534177 -15.821609
1.2032688 -0.35080156 1.2629458 -12.643498 -2.5758228
-11.343508 2.3385992 -8.719341 14.213509 15.404744
-0.39327756 6.338786 2.688887 8.7104025 17.469526
-8.77959 7.0576906 4.648855 -1.3089896 -23.294737
8.013747 13.891729 -9.926753 5.655307 -5.9422326
-22.842539 0.6293588 -18.46266 -10.811862 9.8192625
3.0070958 3.8072643 -2.3861165 3.0821571 -14.739942
1.7594414 -0.6485091 4.485623 2.0207152 7.264915
-6.40137 23.63524 2.9711294 -22.708025 9.93719
20.354511 -10.324688 -0.700492 -8.783211 -5.27593
15.999649 3.3004563 12.747926 15.429879 4.7849145
5.6699696 -2.3826702 10.605882 3.9112158 3.1500628
15.859915 -2.1832209 -23.908653 -6.4799504 -4.5365124
-9.224193 14.568347 -10.568833 4.982321 -4.342062
0.0914714 12.645902 -5.74285 -3.2141201 -2.7173362
-6.680575 0.4757669 -5.035051 -6.7964664 16.865469
-11.54324 7.681869 0.44475392 9.708182 -8.932846
0.4123232 -4.361452 1.3948607 9.511665 0.11667654
2.9079323 6.049952 9.275183 -18.078873 6.2983274
-0.7500531 -2.725033 -7.6027865 3.3404543 2.990815
4.010979 11.000591 -2.8873312 7.1352735 -16.79663
18.495346 -14.293832 7.89578 2.2714825 22.976387
-4.875734 -3.0836344 -2.9999814 13.751918 6.448228
-11.924197 2.171869 2.0423572 -6.173772 10.778437
25.77281 -4.9495463 14.57806 0.3044315 2.6132357
-7.591999 -2.076944 9.025118 1.7834753 -3.1799617
-4.9401326 23.465864 5.1685796 -9.018578 9.037825
-4.4150195 6.859591 -12.274467 -0.88911164 5.186309
-3.9988663 -13.638606 -9.925445 -0.06329413 -3.6709652
-12.397416 -12.719869 -1.395601 2.1150916 5.7381287
-4.4691963 -3.82819 -0.84233856 -1.1604277 -13.490127
8.731719 -20.778936 -11.495662 5.8033476 -4.752041
10.833007 -6.717991 4.504732 13.4244375 1.1306485
7.3435574 1.400918 14.704036 -9.501399 7.2315617
-6.417456 1.3333273 11.872697 -0.30664724 8.8845
6.5569253 4.7948146 0.03662816 -8.704245 6.224871
-3.2701402 -11.508579 ]
demo [ 1.4217498 5.626253 -5.342073 1.1773866 3.308055
1.756596 5.167894 10.80636 -3.8226728 -5.6141334
2.623845 -0.8072968 1.9635103 -7.3128724 0.01103897
-9.723131 0.6619743 -6.976803 10.213478 7.494748
2.9105635 3.8949256 3.7999806 7.1061673 16.905321
-7.1493764 8.733103 3.4230042 -4.831653 -11.403367
11.232214 7.1274667 -4.2828417 2.452362 -5.130748
-18.177666 -2.6116815 -11.000337 -6.7314315 1.6564683
0.7618269 1.1253023 -2.083836 4.725744 -8.782597
-3.539873 3.814236 5.1420674 2.162061 4.096431
-6.4162116 12.747448 1.9429878 -15.152943 6.417416
16.097002 -9.716668 -1.9920526 -3.3649497 -1.871939
11.567354 3.69788 11.258265 7.442363 9.183411
4.5281515 -1.2417862 4.3959084 6.6727695 5.8898783
7.627124 -0.66919386 -11.889693 -9.208865 -7.4274073
-3.7776625 6.917234 -9.848748 -2.0944717 -5.135116
0.49563864 9.317534 -5.9141874 -1.8098574 -0.11738578
-7.169265 -1.0578263 -5.7216787 -5.1173844 16.137651
-4.473626 7.6624317 -0.55381083 9.631587 -6.4704556
-8.548508 4.3716145 -0.79702514 4.478997 -2.9758704
3.272176 2.8382776 5.134597 -9.190781 -0.5657382
-4.8745747 2.3165567 -5.984303 -2.1798875 0.35541576
-0.31784213 9.493548 2.1144536 4.358092 -12.089823
8.451689 -7.925461 4.6242585 4.4289427 18.692003
-2.6204622 -5.149185 -0.35821092 8.488551 4.981496
-9.32683 -2.2544234 6.6417594 1.2119585 10.977129
16.555033 3.3238444 9.551863 -1.6676947 -0.79539716
-8.605674 -0.47356385 2.6741948 -5.359179 -2.6673796
0.66607 15.443222 4.740594 -3.4725387 11.592567
-2.054497 1.7361217 -8.265324 -9.30447 5.4068313
-1.5180256 -7.746615 -6.089606 0.07112726 -0.34904733
-8.649895 -9.998958 -2.564841 -0.53999114 2.601808
-0.31927416 -1.8815292 -2.07215 -3.4105783 -8.2998085
1.483641 -15.365992 -8.288208 3.8847756 -3.4876456
7.3629923 0.4657332 3.132599 12.438889 -1.8337058
4.532936 2.7264361 10.145339 -6.521951 2.897153
-3.3925855 5.079156 7.759716 4.677565 5.8457737
2.402413 7.7071047 3.9711342 -6.390043 6.1268735
-3.7760346 -11.118123 ]
```

- Python API
Expand All @@ -97,56 +98,57 @@ wget -c https://paddlespeech.bj.bcebos.com/vector/audio/85236145389.wav
audio_emb = vector_executor(
model='ecapatdnn_voxceleb12',
sample_rate=16000,
config=None,
config=None, # Set `config` and `ckpt_path` to None to use pretrained model.
ckpt_path=None,
audio_file='./85236145389.wav',
force_yes=False,
device=paddle.get_device())
print('Audio embedding Result: \n{}'.format(audio_emb))
```

Output:
Output：

```bash
# Vector Result:
[ -5.749211 9.505463 -8.200284 -5.2075014 5.3940268
-3.04878 1.611095 10.127234 -10.534177 -15.821609
1.2032688 -0.35080156 1.2629458 -12.643498 -2.5758228
-11.343508 2.3385992 -8.719341 14.213509 15.404744
-0.39327756 6.338786 2.688887 8.7104025 17.469526
-8.77959 7.0576906 4.648855 -1.3089896 -23.294737
8.013747 13.891729 -9.926753 5.655307 -5.9422326
-22.842539 0.6293588 -18.46266 -10.811862 9.8192625
3.0070958 3.8072643 -2.3861165 3.0821571 -14.739942
1.7594414 -0.6485091 4.485623 2.0207152 7.264915
-6.40137 23.63524 2.9711294 -22.708025 9.93719
20.354511 -10.324688 -0.700492 -8.783211 -5.27593
15.999649 3.3004563 12.747926 15.429879 4.7849145
5.6699696 -2.3826702 10.605882 3.9112158 3.1500628
15.859915 -2.1832209 -23.908653 -6.4799504 -4.5365124
-9.224193 14.568347 -10.568833 4.982321 -4.342062
0.0914714 12.645902 -5.74285 -3.2141201 -2.7173362
-6.680575 0.4757669 -5.035051 -6.7964664 16.865469
-11.54324 7.681869 0.44475392 9.708182 -8.932846
0.4123232 -4.361452 1.3948607 9.511665 0.11667654
2.9079323 6.049952 9.275183 -18.078873 6.2983274
-0.7500531 -2.725033 -7.6027865 3.3404543 2.990815
4.010979 11.000591 -2.8873312 7.1352735 -16.79663
18.495346 -14.293832 7.89578 2.2714825 22.976387
-4.875734 -3.0836344 -2.9999814 13.751918 6.448228
-11.924197 2.171869 2.0423572 -6.173772 10.778437
25.77281 -4.9495463 14.57806 0.3044315 2.6132357
-7.591999 -2.076944 9.025118 1.7834753 -3.1799617
-4.9401326 23.465864 5.1685796 -9.018578 9.037825
-4.4150195 6.859591 -12.274467 -0.88911164 5.186309
-3.9988663 -13.638606 -9.925445 -0.06329413 -3.6709652
-12.397416 -12.719869 -1.395601 2.1150916 5.7381287
-4.4691963 -3.82819 -0.84233856 -1.1604277 -13.490127
8.731719 -20.778936 -11.495662 5.8033476 -4.752041
10.833007 -6.717991 4.504732 13.4244375 1.1306485
7.3435574 1.400918 14.704036 -9.501399 7.2315617
-6.417456 1.3333273 11.872697 -0.30664724 8.8845
6.5569253 4.7948146 0.03662816 -8.704245 6.224871
-3.2701402 -11.508579 ]
Audio embedding Result:
[ 1.4217498 5.626253 -5.342073 1.1773866 3.308055
1.756596 5.167894 10.80636 -3.8226728 -5.6141334
2.623845 -0.8072968 1.9635103 -7.3128724 0.01103897
-9.723131 0.6619743 -6.976803 10.213478 7.494748
2.9105635 3.8949256 3.7999806 7.1061673 16.905321
-7.1493764 8.733103 3.4230042 -4.831653 -11.403367
11.232214 7.1274667 -4.2828417 2.452362 -5.130748
-18.177666 -2.6116815 -11.000337 -6.7314315 1.6564683
0.7618269 1.1253023 -2.083836 4.725744 -8.782597
-3.539873 3.814236 5.1420674 2.162061 4.096431
-6.4162116 12.747448 1.9429878 -15.152943 6.417416
16.097002 -9.716668 -1.9920526 -3.3649497 -1.871939
11.567354 3.69788 11.258265 7.442363 9.183411
4.5281515 -1.2417862 4.3959084 6.6727695 5.8898783
7.627124 -0.66919386 -11.889693 -9.208865 -7.4274073
-3.7776625 6.917234 -9.848748 -2.0944717 -5.135116
0.49563864 9.317534 -5.9141874 -1.8098574 -0.11738578
-7.169265 -1.0578263 -5.7216787 -5.1173844 16.137651
-4.473626 7.6624317 -0.55381083 9.631587 -6.4704556
-8.548508 4.3716145 -0.79702514 4.478997 -2.9758704
3.272176 2.8382776 5.134597 -9.190781 -0.5657382
-4.8745747 2.3165567 -5.984303 -2.1798875 0.35541576
-0.31784213 9.493548 2.1144536 4.358092 -12.089823
8.451689 -7.925461 4.6242585 4.4289427 18.692003
-2.6204622 -5.149185 -0.35821092 8.488551 4.981496
-9.32683 -2.2544234 6.6417594 1.2119585 10.977129
16.555033 3.3238444 9.551863 -1.6676947 -0.79539716
-8.605674 -0.47356385 2.6741948 -5.359179 -2.6673796
0.66607 15.443222 4.740594 -3.4725387 11.592567
-2.054497 1.7361217 -8.265324 -9.30447 5.4068313
-1.5180256 -7.746615 -6.089606 0.07112726 -0.34904733
-8.649895 -9.998958 -2.564841 -0.53999114 2.601808
-0.31927416 -1.8815292 -2.07215 -3.4105783 -8.2998085
1.483641 -15.365992 -8.288208 3.8847756 -3.4876456
7.3629923 0.4657332 3.132599 12.438889 -1.8337058
4.532936 2.7264361 10.145339 -6.521951 2.897153
-3.3925855 5.079156 7.759716 4.677565 5.8457737
2.402413 7.7071047 3.9711342 -6.390043 6.1268735
-3.7760346 -11.118123 ]
```

### 4.Pretrained Models
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