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--- |
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language: "ar" |
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pipeline_tag: automatic-speech-recognition |
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tags: |
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- CTC |
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- Attention |
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- pytorch |
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- Transformer |
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license: "cc-by-nc-4.0" |
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datasets: |
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- MGB-3 |
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- egyptian-arabic-conversational-speech-corpus |
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metrics: |
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- wer |
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model-index: |
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- name: omarxadel/hubert-large-arabic-egyptian |
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results: |
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- task: |
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name: Automatic Speech Recognition |
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type: automatic-speech-recognition |
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metrics: |
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- name: Test WER |
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type: wer |
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value: 25.9 |
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- name: Validation WER |
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type: wer |
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value: 23.5 |
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--- |
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# Arabic Hubert-Large - with CTC fine-tuned on MGB-3 and Egyptian Arabic Conversational Speech Corpus (No LM) |
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This model is a fine-tuned version of [Arabic Hubert-Large](https://huggingface.co/asafaya/hubert-large-arabic). We finetuned this model on the MGB-3 and Egyptian Arabic Conversational Speech Corpus datasets, acheiving a state of the art for Egyptian Arabic with WER of `25.9%`. |
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The original model was pre-trained on 2,000 hours of 16kHz sampled Arabic speech audio. When using the model make sure that your speech input is also sampled at 16Khz, see the original [paper](https://arxiv.org/abs/2106.07447) for more details on the model. |
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The performance of the model on the datasets is the following: |
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| Valid WER | Test WER | |
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|:---------:|:--------:| |
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| 23.55 | 25.59 | |
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# Acknowledgement |
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Model fine-tuning and data processing for this work were performed as a part of a Graduation Project from Faculty of Engineering, Alexandria University, CCE Program. |
