Whisper Transcription Web App

A user-friendly web application for transcribing audio and video files using OpenAI's Whisper model, powered by Gradio and faster-whisper.

Features

• 🎙️ Transcribe audio and video files
• 🚀 GPU acceleration support
• 🌐 Multiple language support
• 📱 Responsive and modern UI
• 🔄 Multiple model options (tiny to large-v3)
• ⚙️ Configurable settings via config.ini

Requirements

• Python 3.8+
• CUDA-capable GPU (recommended)
• FFmpeg (for audio/video processing)

Installation

1. Clone this repository:

git clone <repository-url>
cd whisperapp

2. Create a virtual environment and activate it:

python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

3. Install uv (recommended package installer):

curl -LsSf https://astral.sh/uv/install.sh | sh

4. Install the required packages using uv:

uv pip install -r requirements.txt

Configuration

The application can be configured through the config.ini file. Here are the available settings:

Whisper Settings

• default_model: Default Whisper model to use
• device: Device to use (cuda/cpu)
• compute_type: Computation type (float16/float32)
• beam_size: Beam size for transcription
• vad_filter: Enable/disable voice activity detection

App Settings

• max_duration: Maximum audio duration in seconds
• server_name: Server hostname
• server_port: Server port
• share: Enable/disable public sharing

Models and Languages

• available_models: Comma-separated list of available models
• available_languages: Comma-separated list of supported languages

Usage

1. Start the application:

python app.py

2. Open your web browser and navigate to http://localhost:7860

3. Upload an audio or video file and select your preferred model and language settings

4. Click "Transcribe" and wait for the results

Model Options

• tiny: Fastest, lowest accuracy
• base: Good balance of speed and accuracy
• small: Better accuracy, moderate speed
• medium: High accuracy, slower
• large-v1/v2/v3: Highest accuracy, slowest

Tips

• For better accuracy, use larger models (medium, large)
• Processing time increases with model size
• GPU is recommended for faster processing
• Maximum audio duration is configurable in config.ini
• Use uv for faster package installation and dependency resolution

License

MIT License