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Update README.md

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@@ -7,9 +7,8 @@ metrics:
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  pipeline_tag: automatic-speech-recognition
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  datasets:
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  - MuST-C-en_ar
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- library_name: fairseq
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  tags:
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- - audio
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  - automatic-speech-recognition
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  - speech
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  - speech2text
@@ -31,7 +30,8 @@ enhancing the fidelity of transcriptions in scenarios where punctuation is cruci
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  - **Model type:** transformer encoder- decoder
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  - **Language:** En
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  - **Base model:** SpeechT5-ASR [checkpoint](https://huggingface.co/microsoft/speecht5_asr)
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- - **Finetuning dataset:** [MuST-C-en_ar](https://www.kaggle.com/datasets/sebaeymohamed/must-c-en-ar)
 
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  ## Key Features:
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  Punctuation Sensitivity: The model is specifically engineered to be highly sensitive to punctuation nuances in spoken English, ensuring
 
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  pipeline_tag: automatic-speech-recognition
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  datasets:
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  - MuST-C-en_ar
 
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  tags:
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+ - audio
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  - automatic-speech-recognition
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  - speech
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  - speech2text
 
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  - **Model type:** transformer encoder- decoder
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  - **Language:** En
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  - **Base model:** SpeechT5-ASR [checkpoint](https://huggingface.co/microsoft/speecht5_asr)
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+ - **
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+ Finetuning dataset:** [MuST-C-en_ar](https://www.kaggle.com/datasets/sebaeymohamed/must-c-en-ar)
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  ## Key Features:
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  Punctuation Sensitivity: The model is specifically engineered to be highly sensitive to punctuation nuances in spoken English, ensuring