Download Whisper Tarteel model:

https://huggingface.co/tarteel-ai/whisper-base-ar-quran

Install Python Requirements

pip install -r requirements.txt

Run Flask Server:

python3 local_app.py

Alternatively, if you set up a OpenAI key, you can do inference with the hosted version of Whisper by setting your environment variable using this guide and then running python3 hosted_app.py

Navigate to http://127.0.0.1:5000 to use the app!

• Split up audio into chunks for processing in parallel (every 3 seconds)
  • Add a event / session / recording model to keep track of audio clips and join if necessary
  • On html page, add separate tracks per ayat maybe
  • Remove background noise and parse out non-arabic sections
• Merge outputs together into a summary of what was recited
• Add UI/UX for easy use
• Set up server
• Change to a word based algorithm, from a passage based algorithm to account for repetitions
• Quantize model https://pytorch.org/tutorials/intermediate/dynamic_quantization_bert_tutorial.html#evaluate-the-inference-accuracy-and-time https://huggingface.co/docs/optimum/concept_guides/quantization
• Try out Faster-Whisper (https://github.com/guillaumekln/faster-whisper)
• Word based approach could start using string matching for different roots for bi-grams, tri-grams etc
• Deal with a tree of expanding notes of roots
• stop recording after certain amount of silence 1 minute or so
• Fix the issue when users repeat a verse
  • Potential solution: Remove repetitious phrases
• Look into switching to streamlit
• Add tests and componentize functions

• Whisper model to transcribe speech to arabic using Tarteel AI
• Once transcript is retrieved, we use rapidfuzz for the string matching