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🧠 Whisper Azure Transcription Service

Whisper_Azure is a production-grade setup for deploying WhisperX (OpenAI Whisper + word alignment) using Azure Container Instances (ACI) with GPU acceleration.
The project allows on-demand, fast, and local speech-to-text transcription through a RESTful API, packaged via Docker and ready for scalable usage.

✅ Ideal for teams needing scalable audio transcription without maintaining persistent servers.


🚀 Key Features

  • 🎙️ High-quality transcription with WhisperX
  • 📁 Upload audio files (MP3, WAV, etc.) for transcription
  • 🧠 Word-level alignment and diarization support
  • ☁️ Hosted on Azure Container Instances with GPU
  • 🔐 Secured with Azure Identity + Blob Storage
  • 🐳 Docker-based for reproducible local/remote deployment

⚙️ Architecture Overview

Layer Technology
Transcription WhisperX (Python)
API FastAPI
Deployment Docker + Azure CLI
Storage Azure Blob Storage
Auth Azure Managed Identity
Trigger HTTP endpoint (REST API)

📂 Repository Structure

whisper_api/
├── app/
│   ├── main.py         # FastAPI entrypoint
│   ├── transcribe.py   # WhisperX logic
│   └── utils.py        # Helpers (storage, config)
├── Dockerfile
├── requirements.txt
├── azure/
│   └── deploy.sh       # ACI deployment script
└── README.md

🛠️ Setup & Deployment

🔧 Prerequisites

  • Azure CLI (az)
  • Docker
  • An active Azure subscription
  • Python 3.10+
  • WhisperX installed locally (for dev mode)

⚙️ Local Dev Setup

cd whisper_api
python -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt
uvicorn app.main:app --reload

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An Azure function who convert mp3 audio file into a text file on Azure cloud Storage

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