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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. |
