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--- |
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title: Arabic Transcriber Pro |
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emoji: 🗣️ |
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colorFrom: green |
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colorTo: red |
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sdk: streamlit |
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sdk_version: 1.48.0 |
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app_file: app.py |
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pinned: true |
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--- |
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# 🎙️ Arabic Transcriber Pro |
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> **Convert Arabic speech to text with precision — powered by NVIDIA NeMo and Streamlit.** |
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> ✨ Live Demo: [https://huggingface.co/spaces/NightPrince/Arabic-ASR](https://huggingface.co/spaces/NightPrince/Arabic-ASR) |
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> 🔗 Portfolio: [https://nightprincey.github.io/Portfolio/](https://nightprincey.github.io/Portfolio/) |
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<div align="center"> |
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<img src="https://img.shields.io/badge/Python-3.8%2B-blue?style=for-the-badge&logo=python" /> |
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<img src="https://img.shields.io/badge/Streamlit-1.28.0+-orange?style=for-the-badge&logo=streamlit" /> |
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<img src="https://img.shields.io/badge/NVIDIA%20NeMo-ASR%20Model-blueviolet?style=for-the-badge&logo=nvidia" /> |
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<img src="https://img.shields.io/badge/Hugging%20Face-Spaces-FF4B4B?style=for-the-badge&logo=huggingface" /> |
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<img src="https://img.shields.io/badge/License-MIT-green?style=for-the-badge" /> |
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</div> |
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<br /> |
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*Screenshot: Gloomy-elegant UI with real-time transcription and audio visualization* |
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--- |
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## 🌟 Overview |
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**Arabic Transcriber Pro** is a sleek, AI-powered web application that converts spoken **Arabic audio** into accurate, readable text using **NVIDIA’s state-of-the-art NeMo ASR model**. Designed with a modern, **gloomy-elegant aesthetic**, this tool delivers fast, reliable transcription for podcasts, interviews, lectures, and more — all within a user-friendly Streamlit interface hosted on **Hugging Face Spaces**. |
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Built by **Yahya Alnwsany** — AI Engineer, NLP Specialist, and Hugging Face Ambassador — this project reflects a deep commitment to advancing Arabic NLP and making AI accessible for real-world applications. |
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🔗 **Live Demo**: [https://huggingface.co/spaces/NightPrince/Arabic-ASR](https://huggingface.co/spaces/NightPrince/Arabic-ASR) |
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👤 **Developer Portfolio**: [https://nightprincey.github.io/Portfolio/](https://nightprincey.github.io/Portfolio/) |
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--- |
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## 🔧 Features |
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- ✅ **High-Accuracy Arabic ASR** using `nvidia/stt_ar_fastconformer_hybrid_large_pcd_v1.0` |
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- 🎧 **Multi-Format Support**: WAV, MP3, OGG, FLAC, M4A |
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- 🔄 **Auto Audio Conversion**: Resamples to 16kHz mono WAV for optimal model input |
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- ⚡ **Fast Processing** with real-time progress feedback |
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- 💾 **Downloadable Transcripts** in `.txt` format |
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- 🌐 **Web-Based UI** with Streamlit — no installation needed |
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- 🎨 **Elegant Dark Theme** with RTL-ready Arabic text rendering |
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- 📊 **Audio Metadata Display**: Duration, sample rate, channels |
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- 🚀 **Cached Model Loading** for improved performance |
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--- |
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## 🖼️ UI Design Highlights |
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- **Color Palette**: Deep navy (`#0b132b`, `#1c2541`) with teal (`#5bc0be`) and coral (`#e55934`) accents |
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- **Typography**: Clean, modern sans-serif with RTL support |
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- **Interactive Elements**: Smooth progress bars, hover effects, and responsive layout |
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- **Responsive Cards & Gradient Headers** for professional feel |
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--- |
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## 🛠️ Tech Stack |
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| Component | Technology | |
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|------------------|----------| |
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| Frontend | [Streamlit](https://streamlit.io) | |
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| ASR Engine | [NVIDIA NeMo](https://github.com/NVIDIA/NeMo) | |
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| Audio Processing | `pydub`, `soundfile` | |
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| Styling | Custom CSS (Dark Theme, RTL Support) | |
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| Hosting | [Hugging Face Spaces](https://huggingface.co/spaces) | |
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| Deployment | Docker / Streamlit / Git | |
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--- |
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## ▶️ Try It Live |
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Visit the live app on Hugging Face: |
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👉 [https://huggingface.co/spaces/NightPrince/Arabic-ASR](https://huggingface.co/spaces/NightPrince/Arabic-ASR) |
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No setup required — just upload an Arabic audio file and get instant transcription. |
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--- |
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## 📦 Project Structure |
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```python |
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Arabic-transcriber-pro/ |
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│ |
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├── app.py # Main Streamlit application |
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├── requirements.txt # Python dependencies |
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├── README.md # This file |
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``` |
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--- |
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## 📂 Supported Audio Formats |
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| Format | Extension | Notes | |
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|-------|----------|-------| |
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| WAV | `.wav` | Native support | |
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| MP3 | `.mp3` | Requires `ffmpeg` | |
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| OGG | `.ogg` | Vorbis/Opus | |
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| FLAC | `.flac` | Lossless | |
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| M4A | `.m4a` | AAC audio | |
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> 🔁 All files are automatically converted to **16kHz mono WAV** before transcription. |
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--- |
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## About the Developer |
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### 👤 [Yahya Alnwsany](https://nightprincey.github.io/Portfolio/)"# Arabic-Transcriber-Pro" |
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