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  # Sharif-wav2vec2
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- This is the fine-tuned version of Sharif Wav2vec2 for Farsi. The base model was fine-tuned on 108 hours of Commonvoice's Farsi samples with a sampling rate equal to 16kHz. Afterward, we trained a 5gram using [kenlm](https://github.com/kpu/kenlm) toolkit and used it in the processor which increased our accuracy on online ASR. When using the model make sure that your speech input is sampled at 16Khz. Prior to the usage, you may need to install the below dependencies:
 
 
 
 
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  ```shell
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  pip install pyctcdecode
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  *Result (WER)*:
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- | "clean" | "other" |
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  |---|---|
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  | 3.4 | 8.6 |
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  ## Citation
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  If you want to cite this model you can use this:
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  # Sharif-wav2vec2
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+ This is the fine-tuned version of Sharif Wav2vec2 for Farsi. The base model was fine-tuned on 108 hours of Commonvoice's Farsi samples with a sampling rate equal to 16kHz. Afterward, we trained a 5gram using [kenlm](https://github.com/kpu/kenlm) toolkit and used it in the processor which increased our accuracy on online ASR.
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+
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+ ## Usage
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+
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+ When using the model make sure that your speech input is sampled at 16Khz. Prior to the usage, you may need to install the below dependencies:
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  ```shell
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  pip install pyctcdecode
 
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  *Result (WER)*:
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+ | clean | other |
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  |---|---|
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  | 3.4 | 8.6 |
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+ ## Evaluation
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+
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+ For the evaluation use the code below:
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+ ```python
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+ ?
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+ ```
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+
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  ## Citation
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  If you want to cite this model you can use this:
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