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  license: apache-2.0
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- This repository contains a fine-tuned Wav2Vec2 model that has been trained on a small TIMIT dataset for speech recognition tasks. The model achieved a Word Error Rate (WER) of 0.3, indicating promising performance on the given dataset.
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  You can utilize this model for further research and experimentation in the field of speech recognition.
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  In the near future, I plan to expand the collection of fine-tuned Wav2Vec2 models to include various Indian languages. Stay tuned for updates and additions to this repository.
 
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  license: apache-2.0
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+ This repository contains a fine-tuned Wav2Vec2 model that has been trained on a small TIMIT dataset for speech recognition tasks. The model achieved a Word Error Rate (WER) of 30, indicating promising performance on the given small dataset.
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  You can utilize this model for further research and experimentation in the field of speech recognition.
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  In the near future, I plan to expand the collection of fine-tuned Wav2Vec2 models to include various Indian languages. Stay tuned for updates and additions to this repository.