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
• 📺 YouTube video support with subtitle extraction

Requirements

• Python 3.10+
• CUDA-capable GPU (recommended)
• FFmpeg (for audio/video processing)
• uv package manager

Installation

1. Clone this repository:

git clone <repository-url>
cd whisperapp

2. Install uv (if you just pip install you might break your environment):

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

3. Create a venv with uv:

uv venv --python=3.10

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. Choose between two tabs:

   • Local File: Upload and transcribe audio/video files
   • YouTube: Process YouTube videos with subtitle extraction

Local File Tab

1. Upload an audio or video file
2. Select your preferred model and language settings
3. Click "Transcribe" and wait for the results

YouTube Tab

1. Enter a YouTube URL (supports youtube.com, youtu.be, and invidious URLs)
2. Select your preferred model and language settings
3. Click "Process Video"
4. The app will:
   • First try to extract available subtitles
   • If no subtitles are available, download and transcribe the video

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
• YouTube videos will first try to use available subtitles
• If no subtitles are available, the video will be transcribed

License

MIT License