Project Type: Full-Stack Web Application | Backend: Python, FastAPI | Frontend: React + Tailwind CSS | Tools: Google Speech to Text API, Docker
QuranDetect is a Shazam-inspired web application that identifies Quran Ayahs from user audio recordings. The user is able to upload their audio and immeditaely get a text repsonse back of the corrcelty located Ayah.
🎧 Upload Quran recitation audio
🗣️ Automatic Arabic speech transcription
📖 Fuzzy matching to identify Surah & Ayah
🌍 English translation included
This project combines my interest in software engineering and meaningful real-world applications. It’s an ongoing project focused on learning full-stack development, APIs, and deployment.
# Clone repo
git clone https://github.com/ayata30/Quran2.git
cd qurandetect-frontend # your local folder name
# Backend setup
cd backend
python -m venv venv
source venv/bin/activate # Linux/Mac
venv\Scripts\activate # Windows
pip install -r requirements.txt
uvicorn main:app --reload
# Frontend setup
cd ../frontend
npm install
npm start
<img width="2555" height="1331" alt="image" src="https://github.com/user-attachments/assets/fe097d38-5a0e-496e-ae4a-9cfb224c0328" />