Hui Zhang
3 years ago
committed by
GitHub
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caee809513
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([简体中文](./README_cn.md)|English)
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# Speech Verification)
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## Introduction
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Speaker Verification, refers to the problem of getting a speaker embedding from an audio.
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This demo is an implementation to extract speaker embedding from a specific audio file. It can be done by a single command or a few lines in python using `PaddleSpeech`.
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## Usage
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### 1. Installation
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see [installation](https://github.com/PaddlePaddle/PaddleSpeech/blob/develop/docs/source/install.md).
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You can choose one way from easy, meduim and hard to install paddlespeech.
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### 2. Prepare Input File
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The input of this demo should be a WAV file(`.wav`), and the sample rate must be the same as the model.
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Here are sample files for this demo that can be downloaded:
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```bash
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wget -c https://paddlespeech.bj.bcebos.com/vector/audio/85236145389.wav
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```
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### 3. Usage
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- Command Line(Recommended)
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```bash
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paddlespeech vector --task spk --input 85236145389.wav
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echo -e "demo1 85236145389.wav" > vec.job
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paddlespeech vector --task spk --input vec.job
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echo -e "demo2 85236145389.wav \n demo3 85236145389.wav" | paddlespeech vector --task spk
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```
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Usage:
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```bash
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paddlespeech vector --help
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```
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Arguments:
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- `input`(required): Audio file to recognize.
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- `model`: Model type of vector task. Default: `ecapatdnn_voxceleb12`.
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- `sample_rate`: Sample rate of the model. Default: `16000`.
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- `config`: Config of vector task. Use pretrained model when it is None. Default: `None`.
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- `ckpt_path`: Model checkpoint. Use pretrained model when it is None. Default: `None`.
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- `device`: Choose device to execute model inference. Default: default device of paddlepaddle in current environment.
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Output:
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```bash
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demo {'dim': 192, 'embedding': array([ -5.749211 , 9.505463 , -8.200284 , -5.2075014 ,
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5.3940268 , -3.04878 , 1.611095 , 10.127234 ,
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-10.534177 , -15.821609 , 1.2032688 , -0.35080156,
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1.2629458 , -12.643498 , -2.5758228 , -11.343508 ,
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2.3385992 , -8.719341 , 14.213509 , 15.404744 ,
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-0.39327756, 6.338786 , 2.688887 , 8.7104025 ,
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17.469526 , -8.77959 , 7.0576906 , 4.648855 ,
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-1.3089896 , -23.294737 , 8.013747 , 13.891729 ,
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-9.926753 , 5.655307 , -5.9422326 , -22.842539 ,
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0.6293588 , -18.46266 , -10.811862 , 9.8192625 ,
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3.0070958 , 3.8072643 , -2.3861165 , 3.0821571 ,
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-14.739942 , 1.7594414 , -0.6485091 , 4.485623 ,
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2.0207152 , 7.264915 , -6.40137 , 23.63524 ,
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2.9711294 , -22.708025 , 9.93719 , 20.354511 ,
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-10.324688 , -0.700492 , -8.783211 , -5.27593 ,
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15.999649 , 3.3004563 , 12.747926 , 15.429879 ,
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4.7849145 , 5.6699696 , -2.3826702 , 10.605882 ,
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3.9112158 , 3.1500628 , 15.859915 , -2.1832209 ,
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-23.908653 , -6.4799504 , -4.5365124 , -9.224193 ,
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14.568347 , -10.568833 , 4.982321 , -4.342062 ,
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0.0914714 , 12.645902 , -5.74285 , -3.2141201 ,
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-2.7173362 , -6.680575 , 0.4757669 , -5.035051 ,
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-6.7964664 , 16.865469 , -11.54324 , 7.681869 ,
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0.44475392, 9.708182 , -8.932846 , 0.4123232 ,
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-4.361452 , 1.3948607 , 9.511665 , 0.11667654,
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2.9079323 , 6.049952 , 9.275183 , -18.078873 ,
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6.2983274 , -0.7500531 , -2.725033 , -7.6027865 ,
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3.3404543 , 2.990815 , 4.010979 , 11.000591 ,
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-2.8873312 , 7.1352735 , -16.79663 , 18.495346 ,
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-14.293832 , 7.89578 , 2.2714825 , 22.976387 ,
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-4.875734 , -3.0836344 , -2.9999814 , 13.751918 ,
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6.448228 , -11.924197 , 2.171869 , 2.0423572 ,
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-6.173772 , 10.778437 , 25.77281 , -4.9495463 ,
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14.57806 , 0.3044315 , 2.6132357 , -7.591999 ,
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-2.076944 , 9.025118 , 1.7834753 , -3.1799617 ,
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-4.9401326 , 23.465864 , 5.1685796 , -9.018578 ,
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9.037825 , -4.4150195 , 6.859591 , -12.274467 ,
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-0.88911164, 5.186309 , -3.9988663 , -13.638606 ,
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-9.925445 , -0.06329413, -3.6709652 , -12.397416 ,
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-12.719869 , -1.395601 , 2.1150916 , 5.7381287 ,
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-4.4691963 , -3.82819 , -0.84233856, -1.1604277 ,
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-13.490127 , 8.731719 , -20.778936 , -11.495662 ,
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5.8033476 , -4.752041 , 10.833007 , -6.717991 ,
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4.504732 , 13.4244375 , 1.1306485 , 7.3435574 ,
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1.400918 , 14.704036 , -9.501399 , 7.2315617 ,
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-6.417456 , 1.3333273 , 11.872697 , -0.30664724,
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8.8845 , 6.5569253 , 4.7948146 , 0.03662816,
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-8.704245 , 6.224871 , -3.2701402 , -11.508579 ],
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dtype=float32)}
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```
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- Python API
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```python
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import paddle
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from paddlespeech.cli import VectorExecutor
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vector_executor = VectorExecutor()
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audio_emb = vector_executor(
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model='ecapatdnn_voxceleb12',
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sample_rate=16000,
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config=None,
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ckpt_path=None,
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audio_file='./85236145389.wav',
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force_yes=False,
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device=paddle.get_device())
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print('Audio embedding Result: \n{}'.format(audio_emb))
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```
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Output:
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```bash
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# Vector Result:
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{'dim': 192, 'embedding': array([ -5.749211 , 9.505463 , -8.200284 , -5.2075014 ,
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5.3940268 , -3.04878 , 1.611095 , 10.127234 ,
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-10.534177 , -15.821609 , 1.2032688 , -0.35080156,
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1.2629458 , -12.643498 , -2.5758228 , -11.343508 ,
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2.3385992 , -8.719341 , 14.213509 , 15.404744 ,
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-0.39327756, 6.338786 , 2.688887 , 8.7104025 ,
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17.469526 , -8.77959 , 7.0576906 , 4.648855 ,
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-1.3089896 , -23.294737 , 8.013747 , 13.891729 ,
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-9.926753 , 5.655307 , -5.9422326 , -22.842539 ,
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0.6293588 , -18.46266 , -10.811862 , 9.8192625 ,
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3.0070958 , 3.8072643 , -2.3861165 , 3.0821571 ,
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-14.739942 , 1.7594414 , -0.6485091 , 4.485623 ,
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2.0207152 , 7.264915 , -6.40137 , 23.63524 ,
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2.9711294 , -22.708025 , 9.93719 , 20.354511 ,
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-10.324688 , -0.700492 , -8.783211 , -5.27593 ,
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15.999649 , 3.3004563 , 12.747926 , 15.429879 ,
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4.7849145 , 5.6699696 , -2.3826702 , 10.605882 ,
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3.9112158 , 3.1500628 , 15.859915 , -2.1832209 ,
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-23.908653 , -6.4799504 , -4.5365124 , -9.224193 ,
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14.568347 , -10.568833 , 4.982321 , -4.342062 ,
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0.0914714 , 12.645902 , -5.74285 , -3.2141201 ,
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-2.7173362 , -6.680575 , 0.4757669 , -5.035051 ,
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-6.7964664 , 16.865469 , -11.54324 , 7.681869 ,
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0.44475392, 9.708182 , -8.932846 , 0.4123232 ,
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-4.361452 , 1.3948607 , 9.511665 , 0.11667654,
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2.9079323 , 6.049952 , 9.275183 , -18.078873 ,
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6.2983274 , -0.7500531 , -2.725033 , -7.6027865 ,
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3.3404543 , 2.990815 , 4.010979 , 11.000591 ,
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-2.8873312 , 7.1352735 , -16.79663 , 18.495346 ,
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-14.293832 , 7.89578 , 2.2714825 , 22.976387 ,
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-4.875734 , -3.0836344 , -2.9999814 , 13.751918 ,
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6.448228 , -11.924197 , 2.171869 , 2.0423572 ,
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-6.173772 , 10.778437 , 25.77281 , -4.9495463 ,
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14.57806 , 0.3044315 , 2.6132357 , -7.591999 ,
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-2.076944 , 9.025118 , 1.7834753 , -3.1799617 ,
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-4.9401326 , 23.465864 , 5.1685796 , -9.018578 ,
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9.037825 , -4.4150195 , 6.859591 , -12.274467 ,
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-0.88911164, 5.186309 , -3.9988663 , -13.638606 ,
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-9.925445 , -0.06329413, -3.6709652 , -12.397416 ,
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-12.719869 , -1.395601 , 2.1150916 , 5.7381287 ,
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-4.4691963 , -3.82819 , -0.84233856, -1.1604277 ,
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-13.490127 , 8.731719 , -20.778936 , -11.495662 ,
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5.8033476 , -4.752041 , 10.833007 , -6.717991 ,
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4.504732 , 13.4244375 , 1.1306485 , 7.3435574 ,
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1.400918 , 14.704036 , -9.501399 , 7.2315617 ,
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-6.417456 , 1.3333273 , 11.872697 , -0.30664724,
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8.8845 , 6.5569253 , 4.7948146 , 0.03662816,
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-8.704245 , 6.224871 , -3.2701402 , -11.508579 ],
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dtype=float32)}
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```
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### 4.Pretrained Models
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Here is a list of pretrained models released by PaddleSpeech that can be used by command and python API:
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| Model | Sample Rate
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| :--- | :---: |
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| ecapatdnn_voxceleb12 | 16k
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@ -0,0 +1,6 @@
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#!/bin/bash
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wget -c https://paddlespeech.bj.bcebos.com/vector/audio/85236145389.wav
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# asr
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paddlespeech vector --task spk --input ./85236145389.wav
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@ -0,0 +1,7 @@
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# VoxCeleb
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## ECAPA-TDNN
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| Model | Number of Params | Release | Config | dim | Test set | Cosine | Cosine + S-Norm |
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| --- | --- | --- | --- | --- | --- | --- | ---- |
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| ECAPA-TDNN | 85M | 0.1.1 | conf/ecapa_tdnn.yaml |192 | test | 1.15 | 1.06 |
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@ -0,0 +1,13 @@
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# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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@ -0,0 +1,13 @@
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# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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@ -0,0 +1,13 @@
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# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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@ -0,0 +1,13 @@
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# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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@ -0,0 +1,13 @@
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# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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