From d064c8196e174ddd91eb379a734bfad2d16b5453 Mon Sep 17 00:00:00 2001 From: xiongxinlei Date: Thu, 7 Apr 2022 15:21:49 +0800 Subject: [PATCH 1/3] update the speaker verification model, test=doc --- demos/speaker_verification/README.md | 223 +++++++++++++++--------- demos/speaker_verification/README_cn.md | 218 ++++++++++++++--------- demos/speaker_verification/run.sh | 4 +- docs/source/released_model.md | 2 +- examples/voxceleb/sv0/RESULT.md | 2 +- paddlespeech/cli/vector/infer.py | 4 +- 6 files changed, 287 insertions(+), 166 deletions(-) diff --git a/demos/speaker_verification/README.md b/demos/speaker_verification/README.md index 8739d402..27413bd8 100644 --- a/demos/speaker_verification/README.md +++ b/demos/speaker_verification/README.md @@ -30,6 +30,11 @@ wget -c https://paddlespeech.bj.bcebos.com/vector/audio/85236145389.wav paddlespeech vector --task spk --input vec.job echo -e "demo2 85236145389.wav \n demo3 85236145389.wav" | paddlespeech vector --task spk + + paddlespeech vector --task score --input "./85236145389.wav ./123456789.wav" + + echo -e "demo4 85236145389.wav 85236145389.wav \n demo5 85236145389.wav 123456789.wav" > vec.job + paddlespeech vector --task score --input vec.job ``` Usage: @@ -38,6 +43,7 @@ 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`. @@ -47,45 +53,45 @@ 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 @@ -97,56 +103,111 @@ 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)) + + test_emb = vector_executor( + model='ecapatdnn_voxceleb12', + sample_rate=16000, + config=None, # Set `config` and `ckpt_path` to None to use pretrained model. + ckpt_path=None, + audio_file='./123456789.wav', + device=paddle.get_device()) + print('Test embedding Result: \n{}'.format(test_emb)) + score = vector_executor.get_embeddings_score(audio_emb, test_emb) + print(f"Eembeddings Score: {score}") ``` - 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 ] + # get the test embedding + Test embedding Result: + [ -1.902964 2.0690894 -8.034194 3.5472693 0.18089125 + 6.9085927 1.4097427 -1.9487704 -10.021278 -0.20755845 + -8.04332 4.344489 2.3200977 -14.306299 5.184692 + -11.55602 -3.8497238 0.6444722 1.2833948 2.6766639 + 0.5878921 0.7946299 1.7207596 2.5791872 14.998469 + -1.3385371 15.031221 -0.8006958 1.99287 -9.52007 + 2.435466 4.003221 -4.33817 -4.898601 -5.304714 + -18.033886 10.790787 -12.784645 -5.641755 2.9761686 + -10.566622 1.4839455 6.152458 -5.7195854 2.8603241 + 6.112133 8.489869 5.5958056 1.2836679 -1.2293907 + 0.89927405 7.0288725 -2.854029 -0.9782962 5.8255906 + 14.905906 -5.025907 0.7866458 -4.2444224 -16.354029 + 10.521315 0.9604709 -3.3257897 7.144871 -13.592733 + -8.568869 -1.7953678 0.26313916 10.916714 -6.9374123 + 1.857403 -6.2746415 2.8154466 -7.2338667 -2.293357 + -0.05452765 5.4287076 5.0849075 -6.690375 -1.6183422 + 3.654291 0.94352573 -9.200294 -5.4749465 -3.5235846 + 1.3420814 4.240421 -2.772944 -2.8451524 16.311104 + 4.2969875 -1.762936 -12.5758915 8.595198 -0.8835239 + -1.5708797 1.568961 1.1413603 3.5032008 -0.45251232 + -6.786333 16.89443 5.3366146 -8.789056 0.6355629 + 3.2579517 -3.328322 7.5969577 0.66025066 -6.550468 + -9.148656 2.020372 -0.4615173 1.1965656 -3.8764873 + 11.6562195 -6.0750933 12.182899 3.2218833 0.81969476 + 5.570001 -3.8459578 -7.205299 7.9262037 -7.6611166 + -5.249467 -2.2671914 7.2658715 -13.298164 4.821147 + -2.7263982 11.691089 -3.8918593 -2.838112 -1.0336838 + -3.8034165 2.8536487 -5.60398 -1.1972581 1.3455094 + -3.4903061 2.2408795 5.5010734 -3.970756 11.99696 + -7.8858757 0.43160373 -5.5059714 4.3426995 16.322706 + 11.635366 0.72157705 -9.245714 -3.91465 -4.449838 + -1.5716927 7.713747 -2.2430465 -6.198303 -13.481864 + 2.8156567 -5.7812386 5.1456156 2.7289324 -14.505571 + 13.270688 3.448231 -7.0659585 4.5886116 -4.466099 + -0.296428 -11.463529 -2.6076477 14.110243 -6.9725137 + -1.9962958 2.7119343 19.391657 0.01961198 14.607133 + -1.6695905 -4.391516 1.3131028 -6.670972 -5.888604 + 12.0612335 5.9285784 3.3715196 1.492534 10.723728 + -0.95514804 -12.085431 ] + # get the score between enroll and test + Eembeddings Score: 0.4292638301849365 ``` ### 4.Pretrained Models diff --git a/demos/speaker_verification/README_cn.md b/demos/speaker_verification/README_cn.md index fe8949b3..068802fd 100644 --- a/demos/speaker_verification/README_cn.md +++ b/demos/speaker_verification/README_cn.md @@ -29,6 +29,11 @@ wget -c https://paddlespeech.bj.bcebos.com/vector/audio/85236145389.wav paddlespeech vector --task spk --input vec.job echo -e "demo2 85236145389.wav \n demo3 85236145389.wav" | paddlespeech vector --task spk + + paddlespeech vector --task score --input "./85236145389.wav ./123456789.wav" + + echo -e "demo4 85236145389.wav 85236145389.wav \n demo5 85236145389.wav 123456789.wav" > vec.job + paddlespeech vector --task score --input vec.job ``` 使用方法： @@ -37,6 +42,7 @@ wget -c https://paddlespeech.bj.bcebos.com/vector/audio/85236145389.wav ``` 参数： - `input`(必须输入)：用于识别的音频文件。 + - `task` (必须输入): 用于指定 `vector` 处理的具体任务，默认是 `spk`。 - `model`：声纹任务的模型，默认值：`ecapatdnn_voxceleb12`。 - `sample_rate`：音频采样率，默认值：`16000`。 - `config`：声纹任务的参数文件，若不设置则使用预训练模型中的默认配置，默认值：`None`。 @@ -45,45 +51,45 @@ wget -c https://paddlespeech.bj.bcebos.com/vector/audio/85236145389.wav 输出： ```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 @@ -98,53 +104,107 @@ wget -c https://paddlespeech.bj.bcebos.com/vector/audio/85236145389.wav 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)) + + test_emb = vector_executor( + model='ecapatdnn_voxceleb12', + sample_rate=16000, + config=None, # Set `config` and `ckpt_path` to None to use pretrained model. + ckpt_path=None, + audio_file='./123456789.wav', + device=paddle.get_device()) + print('Test embedding Result: \n{}'.format(test_emb)) + score = vector_executor.get_embeddings_score(audio_emb, test_emb) + print(f"Eembeddings Score: {score}") ``` 输出： ```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 ] + # get the test embedding + Test embedding Result: + [ -1.902964 2.0690894 -8.034194 3.5472693 0.18089125 + 6.9085927 1.4097427 -1.9487704 -10.021278 -0.20755845 + -8.04332 4.344489 2.3200977 -14.306299 5.184692 + -11.55602 -3.8497238 0.6444722 1.2833948 2.6766639 + 0.5878921 0.7946299 1.7207596 2.5791872 14.998469 + -1.3385371 15.031221 -0.8006958 1.99287 -9.52007 + 2.435466 4.003221 -4.33817 -4.898601 -5.304714 + -18.033886 10.790787 -12.784645 -5.641755 2.9761686 + -10.566622 1.4839455 6.152458 -5.7195854 2.8603241 + 6.112133 8.489869 5.5958056 1.2836679 -1.2293907 + 0.89927405 7.0288725 -2.854029 -0.9782962 5.8255906 + 14.905906 -5.025907 0.7866458 -4.2444224 -16.354029 + 10.521315 0.9604709 -3.3257897 7.144871 -13.592733 + -8.568869 -1.7953678 0.26313916 10.916714 -6.9374123 + 1.857403 -6.2746415 2.8154466 -7.2338667 -2.293357 + -0.05452765 5.4287076 5.0849075 -6.690375 -1.6183422 + 3.654291 0.94352573 -9.200294 -5.4749465 -3.5235846 + 1.3420814 4.240421 -2.772944 -2.8451524 16.311104 + 4.2969875 -1.762936 -12.5758915 8.595198 -0.8835239 + -1.5708797 1.568961 1.1413603 3.5032008 -0.45251232 + -6.786333 16.89443 5.3366146 -8.789056 0.6355629 + 3.2579517 -3.328322 7.5969577 0.66025066 -6.550468 + -9.148656 2.020372 -0.4615173 1.1965656 -3.8764873 + 11.6562195 -6.0750933 12.182899 3.2218833 0.81969476 + 5.570001 -3.8459578 -7.205299 7.9262037 -7.6611166 + -5.249467 -2.2671914 7.2658715 -13.298164 4.821147 + -2.7263982 11.691089 -3.8918593 -2.838112 -1.0336838 + -3.8034165 2.8536487 -5.60398 -1.1972581 1.3455094 + -3.4903061 2.2408795 5.5010734 -3.970756 11.99696 + -7.8858757 0.43160373 -5.5059714 4.3426995 16.322706 + 11.635366 0.72157705 -9.245714 -3.91465 -4.449838 + -1.5716927 7.713747 -2.2430465 -6.198303 -13.481864 + 2.8156567 -5.7812386 5.1456156 2.7289324 -14.505571 + 13.270688 3.448231 -7.0659585 4.5886116 -4.466099 + -0.296428 -11.463529 -2.6076477 14.110243 -6.9725137 + -1.9962958 2.7119343 19.391657 0.01961198 14.607133 + -1.6695905 -4.391516 1.3131028 -6.670972 -5.888604 + 12.0612335 5.9285784 3.3715196 1.492534 10.723728 + -0.95514804 -12.085431 ] + # get the score between enroll and test + Eembeddings Score: 0.4292638301849365 ``` ### 4.预训练模型 diff --git a/demos/speaker_verification/run.sh b/demos/speaker_verification/run.sh index 856886d3..23ca8eb4 100644 --- a/demos/speaker_verification/run.sh +++ b/demos/speaker_verification/run.sh @@ -2,5 +2,5 @@ wget -c https://paddlespeech.bj.bcebos.com/vector/audio/85236145389.wav -# asr -paddlespeech vector --task spk --input ./85236145389.wav \ No newline at end of file +# vector +paddlespeech vector --task spk --input ./85236145389.wav diff --git a/docs/source/released_model.md b/docs/source/released_model.md index 9a423e03..48ceaf84 100644 --- a/docs/source/released_model.md +++ b/docs/source/released_model.md @@ -80,7 +80,7 @@ PANN | ESC-50 |[pann-esc50](../../examples/esc50/cls0)|[esc50_cnn6.tar.gz](https Model Type | Dataset| Example Link | Pretrained Models | Static Models :-------------:| :------------:| :-----: | :-----: | :-----: -PANN | VoxCeleb| [voxceleb_ecapatdnn](https://github.com/PaddlePaddle/PaddleSpeech/tree/develop/examples/voxceleb/sv0) | [ecapatdnn.tar.gz](https://paddlespeech.bj.bcebos.com/vector/voxceleb/sv0_ecapa_tdnn_voxceleb12_ckpt_0_1_1.tar.gz) | - +PANN | VoxCeleb| [voxceleb_ecapatdnn](https://github.com/PaddlePaddle/PaddleSpeech/tree/develop/examples/voxceleb/sv0) | [ecapatdnn.tar.gz](https://paddlespeech.bj.bcebos.com/vector/voxceleb/sv0_ecapa_tdnn_voxceleb12_ckpt_0_2_0.tar.gz) | - ## Punctuation Restoration Models Model Type | Dataset| Example Link | Pretrained Models diff --git a/examples/voxceleb/sv0/RESULT.md b/examples/voxceleb/sv0/RESULT.md index c37bcece..3a3f67d0 100644 --- a/examples/voxceleb/sv0/RESULT.md +++ b/examples/voxceleb/sv0/RESULT.md @@ -4,4 +4,4 @@ | Model | Number of Params | Release | Config | dim | Test set | Cosine | Cosine + S-Norm | | --- | --- | --- | --- | --- | --- | --- | ---- | -| ECAPA-TDNN | 85M | 0.1.1 | conf/ecapa_tdnn.yaml |192 | test | 1.15 | 1.06 | +| ECAPA-TDNN | 85M | 0.2.0 | conf/ecapa_tdnn.yaml |192 | test | 1.02 | 0.95 | diff --git a/paddlespeech/cli/vector/infer.py b/paddlespeech/cli/vector/infer.py index 175a9723..52f4f207 100644 --- a/paddlespeech/cli/vector/infer.py +++ b/paddlespeech/cli/vector/infer.py @@ -42,9 +42,9 @@ pretrained_models = { # "paddlespeech vector --task spk --model ecapatdnn_voxceleb12-16k --sr 16000 --input ./input.wav" "ecapatdnn_voxceleb12-16k": { 'url': - 'https://paddlespeech.bj.bcebos.com/vector/voxceleb/sv0_ecapa_tdnn_voxceleb12_ckpt_0_1_1.tar.gz', + 'https://paddlespeech.bj.bcebos.com/vector/voxceleb/sv0_ecapa_tdnn_voxceleb12_ckpt_0_2_0.tar.gz', 'md5': - 'a1c0dba7d4de997187786ff517d5b4ec', + 'cc33023c54ab346cd318408f43fcaf95', 'cfg_path': 'conf/model.yaml', # the yaml config path 'ckpt_path': From 2a095db22ef842344b2e1ffe170eb29aa0757a64 Mon Sep 17 00:00:00 2001 From: xiongxinlei Date: Thu, 7 Apr 2022 15:27:32 +0800 Subject: [PATCH 2/3] remove unuse content in readme, test=doc --- demos/speaker_verification/README.md | 59 ------------------------- demos/speaker_verification/README_cn.md | 54 ---------------------- 2 files changed, 113 deletions(-) diff --git a/demos/speaker_verification/README.md b/demos/speaker_verification/README.md index 27413bd8..71fbbfe0 100644 --- a/demos/speaker_verification/README.md +++ b/demos/speaker_verification/README.md @@ -30,11 +30,6 @@ wget -c https://paddlespeech.bj.bcebos.com/vector/audio/85236145389.wav paddlespeech vector --task spk --input vec.job echo -e "demo2 85236145389.wav \n demo3 85236145389.wav" | paddlespeech vector --task spk - - paddlespeech vector --task score --input "./85236145389.wav ./123456789.wav" - - echo -e "demo4 85236145389.wav 85236145389.wav \n demo5 85236145389.wav 123456789.wav" > vec.job - paddlespeech vector --task score --input vec.job ``` Usage: @@ -108,17 +103,6 @@ wget -c https://paddlespeech.bj.bcebos.com/vector/audio/85236145389.wav audio_file='./85236145389.wav', device=paddle.get_device()) print('Audio embedding Result: \n{}'.format(audio_emb)) - - test_emb = vector_executor( - model='ecapatdnn_voxceleb12', - sample_rate=16000, - config=None, # Set `config` and `ckpt_path` to None to use pretrained model. - ckpt_path=None, - audio_file='./123456789.wav', - device=paddle.get_device()) - print('Test embedding Result: \n{}'.format(test_emb)) - score = vector_executor.get_embeddings_score(audio_emb, test_emb) - print(f"Eembeddings Score: {score}") ``` Output： @@ -165,49 +149,6 @@ wget -c https://paddlespeech.bj.bcebos.com/vector/audio/85236145389.wav -3.3925855 5.079156 7.759716 4.677565 5.8457737 2.402413 7.7071047 3.9711342 -6.390043 6.1268735 -3.7760346 -11.118123 ] - # get the test embedding - Test embedding Result: - [ -1.902964 2.0690894 -8.034194 3.5472693 0.18089125 - 6.9085927 1.4097427 -1.9487704 -10.021278 -0.20755845 - -8.04332 4.344489 2.3200977 -14.306299 5.184692 - -11.55602 -3.8497238 0.6444722 1.2833948 2.6766639 - 0.5878921 0.7946299 1.7207596 2.5791872 14.998469 - -1.3385371 15.031221 -0.8006958 1.99287 -9.52007 - 2.435466 4.003221 -4.33817 -4.898601 -5.304714 - -18.033886 10.790787 -12.784645 -5.641755 2.9761686 - -10.566622 1.4839455 6.152458 -5.7195854 2.8603241 - 6.112133 8.489869 5.5958056 1.2836679 -1.2293907 - 0.89927405 7.0288725 -2.854029 -0.9782962 5.8255906 - 14.905906 -5.025907 0.7866458 -4.2444224 -16.354029 - 10.521315 0.9604709 -3.3257897 7.144871 -13.592733 - -8.568869 -1.7953678 0.26313916 10.916714 -6.9374123 - 1.857403 -6.2746415 2.8154466 -7.2338667 -2.293357 - -0.05452765 5.4287076 5.0849075 -6.690375 -1.6183422 - 3.654291 0.94352573 -9.200294 -5.4749465 -3.5235846 - 1.3420814 4.240421 -2.772944 -2.8451524 16.311104 - 4.2969875 -1.762936 -12.5758915 8.595198 -0.8835239 - -1.5708797 1.568961 1.1413603 3.5032008 -0.45251232 - -6.786333 16.89443 5.3366146 -8.789056 0.6355629 - 3.2579517 -3.328322 7.5969577 0.66025066 -6.550468 - -9.148656 2.020372 -0.4615173 1.1965656 -3.8764873 - 11.6562195 -6.0750933 12.182899 3.2218833 0.81969476 - 5.570001 -3.8459578 -7.205299 7.9262037 -7.6611166 - -5.249467 -2.2671914 7.2658715 -13.298164 4.821147 - -2.7263982 11.691089 -3.8918593 -2.838112 -1.0336838 - -3.8034165 2.8536487 -5.60398 -1.1972581 1.3455094 - -3.4903061 2.2408795 5.5010734 -3.970756 11.99696 - -7.8858757 0.43160373 -5.5059714 4.3426995 16.322706 - 11.635366 0.72157705 -9.245714 -3.91465 -4.449838 - -1.5716927 7.713747 -2.2430465 -6.198303 -13.481864 - 2.8156567 -5.7812386 5.1456156 2.7289324 -14.505571 - 13.270688 3.448231 -7.0659585 4.5886116 -4.466099 - -0.296428 -11.463529 -2.6076477 14.110243 -6.9725137 - -1.9962958 2.7119343 19.391657 0.01961198 14.607133 - -1.6695905 -4.391516 1.3131028 -6.670972 -5.888604 - 12.0612335 5.9285784 3.3715196 1.492534 10.723728 - -0.95514804 -12.085431 ] - # get the score between enroll and test - Eembeddings Score: 0.4292638301849365 ``` ### 4.Pretrained Models diff --git a/demos/speaker_verification/README_cn.md b/demos/speaker_verification/README_cn.md index 068802fd..183be942 100644 --- a/demos/speaker_verification/README_cn.md +++ b/demos/speaker_verification/README_cn.md @@ -106,17 +106,6 @@ wget -c https://paddlespeech.bj.bcebos.com/vector/audio/85236145389.wav audio_file='./85236145389.wav', device=paddle.get_device()) print('Audio embedding Result: \n{}'.format(audio_emb)) - - test_emb = vector_executor( - model='ecapatdnn_voxceleb12', - sample_rate=16000, - config=None, # Set `config` and `ckpt_path` to None to use pretrained model. - ckpt_path=None, - audio_file='./123456789.wav', - device=paddle.get_device()) - print('Test embedding Result: \n{}'.format(test_emb)) - score = vector_executor.get_embeddings_score(audio_emb, test_emb) - print(f"Eembeddings Score: {score}") ``` 输出： @@ -162,49 +151,6 @@ wget -c https://paddlespeech.bj.bcebos.com/vector/audio/85236145389.wav -3.3925855 5.079156 7.759716 4.677565 5.8457737 2.402413 7.7071047 3.9711342 -6.390043 6.1268735 -3.7760346 -11.118123 ] - # get the test embedding - Test embedding Result: - [ -1.902964 2.0690894 -8.034194 3.5472693 0.18089125 - 6.9085927 1.4097427 -1.9487704 -10.021278 -0.20755845 - -8.04332 4.344489 2.3200977 -14.306299 5.184692 - -11.55602 -3.8497238 0.6444722 1.2833948 2.6766639 - 0.5878921 0.7946299 1.7207596 2.5791872 14.998469 - -1.3385371 15.031221 -0.8006958 1.99287 -9.52007 - 2.435466 4.003221 -4.33817 -4.898601 -5.304714 - -18.033886 10.790787 -12.784645 -5.641755 2.9761686 - -10.566622 1.4839455 6.152458 -5.7195854 2.8603241 - 6.112133 8.489869 5.5958056 1.2836679 -1.2293907 - 0.89927405 7.0288725 -2.854029 -0.9782962 5.8255906 - 14.905906 -5.025907 0.7866458 -4.2444224 -16.354029 - 10.521315 0.9604709 -3.3257897 7.144871 -13.592733 - -8.568869 -1.7953678 0.26313916 10.916714 -6.9374123 - 1.857403 -6.2746415 2.8154466 -7.2338667 -2.293357 - -0.05452765 5.4287076 5.0849075 -6.690375 -1.6183422 - 3.654291 0.94352573 -9.200294 -5.4749465 -3.5235846 - 1.3420814 4.240421 -2.772944 -2.8451524 16.311104 - 4.2969875 -1.762936 -12.5758915 8.595198 -0.8835239 - -1.5708797 1.568961 1.1413603 3.5032008 -0.45251232 - -6.786333 16.89443 5.3366146 -8.789056 0.6355629 - 3.2579517 -3.328322 7.5969577 0.66025066 -6.550468 - -9.148656 2.020372 -0.4615173 1.1965656 -3.8764873 - 11.6562195 -6.0750933 12.182899 3.2218833 0.81969476 - 5.570001 -3.8459578 -7.205299 7.9262037 -7.6611166 - -5.249467 -2.2671914 7.2658715 -13.298164 4.821147 - -2.7263982 11.691089 -3.8918593 -2.838112 -1.0336838 - -3.8034165 2.8536487 -5.60398 -1.1972581 1.3455094 - -3.4903061 2.2408795 5.5010734 -3.970756 11.99696 - -7.8858757 0.43160373 -5.5059714 4.3426995 16.322706 - 11.635366 0.72157705 -9.245714 -3.91465 -4.449838 - -1.5716927 7.713747 -2.2430465 -6.198303 -13.481864 - 2.8156567 -5.7812386 5.1456156 2.7289324 -14.505571 - 13.270688 3.448231 -7.0659585 4.5886116 -4.466099 - -0.296428 -11.463529 -2.6076477 14.110243 -6.9725137 - -1.9962958 2.7119343 19.391657 0.01961198 14.607133 - -1.6695905 -4.391516 1.3131028 -6.670972 -5.888604 - 12.0612335 5.9285784 3.3715196 1.492534 10.723728 - -0.95514804 -12.085431 ] - # get the score between enroll and test - Eembeddings Score: 0.4292638301849365 ``` ### 4.预训练模型 From 85e4e70605b7e76461f08917ce67c25abd8ad232 Mon Sep 17 00:00:00 2001 From: xiongxinlei Date: Thu, 7 Apr 2022 15:29:28 +0800 Subject: [PATCH 3/3] remove score content, test=doc --- demos/speaker_verification/README_cn.md | 5 ----- 1 file changed, 5 deletions(-) diff --git a/demos/speaker_verification/README_cn.md b/demos/speaker_verification/README_cn.md index 183be942..8b542b20 100644 --- a/demos/speaker_verification/README_cn.md +++ b/demos/speaker_verification/README_cn.md @@ -29,11 +29,6 @@ wget -c https://paddlespeech.bj.bcebos.com/vector/audio/85236145389.wav paddlespeech vector --task spk --input vec.job echo -e "demo2 85236145389.wav \n demo3 85236145389.wav" | paddlespeech vector --task spk - - paddlespeech vector --task score --input "./85236145389.wav ./123456789.wav" - - echo -e "demo4 85236145389.wav 85236145389.wav \n demo5 85236145389.wav 123456789.wav" > vec.job - paddlespeech vector --task score --input vec.job ``` 使用方法：