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---
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.