AbdirahmanNomad/IqraAI

Quran speech recognition (ASR) with verse matching, Iqra mode, and translations in Arabic, English, Somali, Amharic & Swahili. Built with Tarteel Whisper. # Iqra AI World-class Quran speech recognition with Tarteel-style mistake detection, Iqra/memorization mode, and multilingual translations. **Languages:** Arabic · English · Somali · Amharic · Swahili **Author:** Abdirahman Ahmed · Offered as sadaqa jariyah ## Contents - Features - Build with Iqra AI - Quick Start - Project Structure - Tabs - Languages - Data Sources - Requirements - Contributing - Images - Acknowledgements - License --- ## Features - **ASR** — Tarteel whisper-base-ar-quran (fine-tuned for Quranic Arabic) - **Verse matching & mistake detection** — Green (correct), red (missed/incorrect), yellow (extra) - **Iqra mode** — Pick Surah:Ayah, recite, compare with canonical text and see mistakes - **Translations** — Arabic, English, Somali, Amharic, Swahili via Quran Enc - **Letter practice** — Hijaiyah letter classification - **Export** — TXT, JSON, SRT via CLI --- ## Build with Iqra AI After cloning, use the modules to build your own apps: | Build | Use | |-------|-----| | **Quran memorization app** | Import `asr_engine`, `matcher`, `quran_data` → transcribe recitation, match verses, show mistakes. | | **Mobile / web app backend** | Run `app.py` or wrap `transcribe()` + `match_and_analyze()` in your API. | | **Letter learning app** | Use hijaiyah classifier from `app.py` for kids/learners. | --- ## Quick Start > [!TIP] > On first run, Arabic XML and ASR models download automatically. Translations require internet. ### 1. Clone and enter the repo ```bash git clone github.com cd IqraAI ``` ### 2. Set up Python environment ```bash python3 -m venv venv source venv/bin/activate # Mac/Linux # OR on Windows: venv\Scripts\activate pip install -r requirements.txt ``` ### 3. Run the web app ```bash python app.py ``` Open **http://127.0.0.1:7860** in your browser. ### 4. CLI (optional) ```bash python transcribe.py path/to/audio.wav --match --export json ``` > [!NOTE] > First run downloads ~500MB …