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@@ -26,19 +26,7 @@ metrics:
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  This repository provides all the necessary tools to perform command recognition with SpeechBrain using a model pretrained on Google Speech Commands.
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  You can download the dataset [here](https://www.tensorflow.org/datasets/catalog/speech_commands)
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  The dataset provides small training, validation, and test sets useful for detecting single keywords in short audio clips. The provided system can recognize the following 12 keywords:
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-
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- -'yes'
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- -'no'
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- -'up'
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- -'down'
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- -'left'
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- -'right'
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- -'on'
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- -'off'
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- -'stop'
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- -'go'
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- -'unknown'
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- -'silence'
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  For a better experience, we encourage you to learn more about
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  [SpeechBrain](https://speechbrain.github.io). The given model performance on the test set is:
@@ -142,7 +130,7 @@ The SpeechBrain team does not provide any warranty on the performance achieved b
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  year = {2021},
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  publisher = {GitHub},
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  journal = {GitHub repository},
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- howpublished = {\\\\url{https://github.com/speechbrain/speechbrain}},
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  }
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  ```
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  This repository provides all the necessary tools to perform command recognition with SpeechBrain using a model pretrained on Google Speech Commands.
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  You can download the dataset [here](https://www.tensorflow.org/datasets/catalog/speech_commands)
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  The dataset provides small training, validation, and test sets useful for detecting single keywords in short audio clips. The provided system can recognize the following 12 keywords:
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+ 'yes','no','up','down','left','right','on','off','stop','go','unknown','silence'
 
 
 
 
 
 
 
 
 
 
 
 
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  For a better experience, we encourage you to learn more about
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  [SpeechBrain](https://speechbrain.github.io). The given model performance on the test set is:
 
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  year = {2021},
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  publisher = {GitHub},
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  journal = {GitHub repository},
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+ howpublished = {\\\\\\\\url{https://github.com/speechbrain/speechbrain}},
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  }
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  ```
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