This is a project to evaluate the performance of different fine-tuned neural ASR systems.

1. Model Inference Time
2. Word error rate (WER)
3. Match error rate (MER)
4. Word information Preserved (WIP)
5. Character error rate (CER)

1. OpenAI Whisper Large
2. arbml/whisper-largev2-ar
3. tarteel-ai/whisper-base-ar-quran
4. tarteel-ai/whisper-tiny-ar-quran

1. Assuming Conda is installed, create a new conda environment:

conda create -n quranwhisper python=3.10 
conda activate quranwhisper 

2. Install the required packages:

pip install -r requirements.txt 

3. Add the recitation audio files in the root directory of the project, as shown below:

    .
    ├── ...
    ├── recitations                    
    │   ├── aya1.wav          
    │   ├── aya2.wav         
    │   └── ...                
    └── ...