---
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.