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README.md
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name: Automatic Speech Recognition
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type: automatic-speech-recognition
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dataset:
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name: IWSLT-2023, FLEURS, BiteSize, SpokenWords, Tatoeba, and Wikimedia
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well as a copy of the dataset with noise reduction and normalization (for
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both train and test)
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type: ymoslem/IWSLT2023-GA-EN
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metrics:
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- name: Bleu
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# Whisper Small GA-EN Speech Translation
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the IWSLT-2023, FLEURS, BiteSize, SpokenWords, Tatoeba, and Wikimedia as well as a copy of the dataset with noise reduction and normalization (for both train and test) dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.3339
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- Bleu: 30.66
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name: Automatic Speech Recognition
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type: automatic-speech-recognition
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dataset:
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name: IWSLT-2023, FLEURS, BiteSize, SpokenWords, Tatoeba, and Wikimedia, normalized
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type: ymoslem/IWSLT2023-GA-EN
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metrics:
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- name: Bleu
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# Whisper Small GA-EN Speech Translation
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the IWSLT-2023, FLEURS, BiteSize, SpokenWords, Tatoeba, and Wikimedia as well as a copy of the dataset with noise reduction and normalization (for both train and test) dataset.
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The datasets were processed with noise reduction and normalization (both the train and test splits).
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It achieves the following results on the evaluation set:
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- Loss: 1.3339
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- Bleu: 30.66
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