readme: ---
  language: "ar"
  pipeline_tag: automatic-speech-recognition
  tags:
  - CTC
  - Attention
  - pytorch
  - Transformer
  license: "cc-by-nc-4.0"
  datasets:
  - MGB-3
  - egyptian-arabic-conversational-speech-corpus
  metrics:
  - wer
  model-index:
  - name: omarxadel/hubert-large-arabic-egyptian
    results:
    - task: 
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      metrics:
         - name: Test WER
           type: wer
           value: 25.9
         - name: Validation WER
           type: wer
           value: 23.5
  ---
  
  # Arabic Hubert-Large - with CTC fine-tuned on MGB-3 and Egyptian Arabic Conversational Speech Corpus (No LM)
  
  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%`. 
  
  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.
  
  The performance of the model on the datasets is the following:
  
  | Valid WER | Test WER |
  |:---------:|:--------:|
  |   23.55   |  25.59   | 
  
  # Acknowledgement
  
  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.