Audio Analysis & Transcription - Streamlit App

A modern, feature-rich audio analysis and transcription application built with Streamlit. This application provides powerful audio processing capabilities including enhancement, transcription, and AI-powered analysis.

Features

• Audio Analysis: Visualize waveforms and spectrograms
• Audio Enhancement: Noise reduction, normalization, and EQ enhancement
• Transcription: High-quality speech-to-text using Whisper
• AI Enhancement: Improve transcription quality with Claude
• Interactive Chat: AI assistant for audio-related queries
• Multiple Export Formats: TXT, JSON, SRT
• Session Management: Save and restore your work

Installation

1. Clone the repository:

git clone <repository-url>
cd ai-audio

2. Create a virtual environment:

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

3. Install dependencies:

pip install -r requirements.txt

4. Set up environment variables:

cp env.example .env
# Edit .env and add your Anthropic API key

Usage

1. Start the application:

streamlit run main.py

2. Open your browser to http://localhost:8501

3. Upload an audio file using the sidebar

4. Explore the different tabs:

   • Audio Analysis: View waveform and spectrogram
   • Enhancement: Apply audio improvements
   • Transcription: Convert speech to text
   • AI Assistant: Chat about your audio

Project Structure

audio_analyzer/
├── config/           # Configuration and settings
├── core/            # Core processing modules
├── services/        # External service integrations
├── ui/              # UI components and state management
├── utils/           # Utility functions
├── main.py          # Main application entry point
└── requirements.txt # Project dependencies

Configuration

Key settings can be adjusted in config/settings.py:

• MAX_AUDIO_LENGTH: Maximum audio duration (seconds)
• CHUNK_SIZE: Processing chunk size (seconds)
• DEFAULT_SAMPLE_RATE: Default audio sample rate
• MAX_FILE_SIZE_MB: Maximum upload file size

Advanced Features

Custom Enhancement Pipeline

The application supports a customizable enhancement pipeline. You can add or remove processing stages:

from core.enhancement_pipeline import EnhancementPipeline, PipelineStage

pipeline = EnhancementPipeline()
pipeline.add_stage(PipelineStage(
    name="Custom Filter",
    function=my_custom_filter,
    params={'param1': value}
))

Session Management

Save your work for later:

• Use the session manager to save current state
• Load previous sessions from the sidebar
• Export session data for backup

API Keys

This application requires an Anthropic API key for AI features. Get your key from: https://console.anthropic.com/

Troubleshooting

Common Issues

1. Memory Errors: Reduce MAX_AUDIO_LENGTH in settings
2. Slow Processing: Enable GPU in settings if available
3. API Errors: Check your Anthropic API key is valid

Debug Mode

Enable debug mode in .env:

DEBUG=True

Contributing

Contributions are welcome! Please:

1. Fork the repository
2. Create a feature branch
3. Submit a pull request

License

This project is licensed under the MIT License.