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: 29.3755
         - name: Validation WER
           type: wer
           value: 29.1828
  ---
  
  # Wav2Vec2-XLSR-53 - with CTC fine-tuned on MGB-3 and Egyptian Arabic Conversational Speech Corpus (No LM)
  
  This model is a fine-tuned version of [Wav2Vec2-XLSR-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53). We finetuned this model on the MGB-3 and Egyptian Arabic Conversational Speech Corpus datasets, acheiving WER of `29.3755%`. 
  
  The performance of the model on the datasets is the following:
  
  | Valid WER | Test WER |
  |:---------:|:--------:|
  |   29.18   |  29.37  | 
  
  # 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.