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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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  should probably proofread and complete it, then remove this comment. -->
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- # wav2vec2-large-xlsr-persian-asr-shemo_me7494
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  This model is a fine-tuned version of [masoudmzb/wav2vec2-xlsr-multilingual-53-fa](https://huggingface.co/masoudmzb/wav2vec2-xlsr-multilingual-53-fa)
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  on the [ShEMO](https://github.com/pariajm/sharif-emotional-speech-dataset) dataset for speech recognition in Persian (Farsi).
 
 
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  It achieves the following results:
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  - Loss on ShEMO train set: 0.7618
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  - Loss on ShEMO dev set: 0.6728
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  - WER on ShEMO dev set: 32.85
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  - WER on Common Voice 13 test set: 19.21
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- Model description
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-
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  ## Model description
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- ### Model description
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-
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- ### Model description
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-
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- ### Model description
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-
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  More information needed
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  ## Intended uses & limitations
 
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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  should probably proofread and complete it, then remove this comment. -->
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+ # Wav2Vec2 Large XLSR Persian ShEMO
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  This model is a fine-tuned version of [masoudmzb/wav2vec2-xlsr-multilingual-53-fa](https://huggingface.co/masoudmzb/wav2vec2-xlsr-multilingual-53-fa)
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  on the [ShEMO](https://github.com/pariajm/sharif-emotional-speech-dataset) dataset for speech recognition in Persian (Farsi).
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+ When using this model, make sure that your speech input is sampled at 16 kHz.
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+
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  It achieves the following results:
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  - Loss on ShEMO train set: 0.7618
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  - Loss on ShEMO dev set: 0.6728
 
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  - WER on ShEMO dev set: 32.85
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  - WER on Common Voice 13 test set: 19.21
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  ## Model description
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  More information needed
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  ## Intended uses & limitations