Overview
This Tunisian Automatic Speech Recognition (ASR) project focuses on developing a system that can accurately transcribe spoken Tunisian Arabic into text. It's a finetuned on a WavLM (an extension of Wav2Vec 2.0 which uses a transformer architecture ) as a base Model and boosted with a KenLM language model located in language_model/languageModel.arpa.
📈 Performance
Tested On a Private Dataset
| CER | WER |
|---|---|
9.18% |
24.78% |
| A Private Dataset , 2.5 Hours of Tunisian audio data. |
🚀 How To run the web app Locally?
1. Download the repo :
Make sure that you installed the huggingface client before cloning the repo .
> git clone https://huggingface.co/brdhaker3/TunASR
2. install the necessary dependencies :
> pip install -r requirements.txt
3. Adjust the hyperparams.yaml file
Check the hyper parameters file hyperparams.yaml and verify the path of the language model.
4.🌐Run the web app:
To run the web app you have only to execute:
> python app.py
✉️ Contact :
If you have questions, you can send an email to : [email protected]
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Base model
microsoft/wavlm-large