A powerful system for transcribing audio files, analyzing transcripts, and generating creative interpretations of the content. Combines OpenAI's Whisper for transcription with GPT models for analysis, featuring customizable templates and musical transformations.
- Quick Start
- Installation
- Basic Usage
- Templates
- Advanced Features
- Musical Summaries
- Customization
- Troubleshooting
# Install
pip install -r requirements.txt
# Set up environment
cp .env.example .env
# Edit .env with your OpenAI API key
# Basic usage
python main.py your_audio.mp3
# Generate musical summary
python main.py your_audio.mp3 --musical-style hiphop
- Clone the repository:
git clone [repository-url]
cd audio-analysis-system
- Install dependencies:
pip install -r requirements.txt
- Set up your environment:
cp .env.example .env
# Edit .env and add:
OPENAI_API_KEY=your-api-key-here
OPENAI_MODEL=gpt-4 # Optional, defaults to gpt-4o
python main.py path/to/your/audio.mp3
python main.py path/to/your/audio.mp3 --template summary
python main.py path/to/your/audio.mp3 --template summary \
--context "Quarterly planning meeting" \
--focus objectives deadlines
- summary: Concise summary of key points
- technical_specs: Technical analysis and specifications
- hiphop_summary: Hip-hop style interpretation
- country_summary: Country music style interpretation
- ballad_summary: 80s power ballad style interpretation
python main.py --list-templates
python main.py meeting.mp3 --template summary \
--instruction "Focus on action items and deadlines" \
--focus decisions deadlines \
--exclude small-talk
python main.py --create-template my_template \
--template-category custom \
--system-prompt "You are analyzing..." \
--instruction "Analyze the following..." \
--temperature 0.7 \
--description "My custom analysis template"
templates/
├── README.md
├── base/
│ └── musical_summary_base.json
├── analysis/
│ ├── summary.json
│ └── technical_specs.json
├── musical/
│ ├── hiphop_summary.json
│ ├── country_summary.json
│ └── ballad_summary.json
└── custom/
└── your_custom_templates.json
Transform your transcripts into various musical styles while maintaining information integrity.
python main.py meeting.mp3 --musical-style hiphop
python main.py meeting.mp3 --musical-style country --include-original
- Hip-hop: Complex rhyme schemes and wordplay
- Country: Narrative-driven storytelling
- Power Ballad: 80s-style emotional interpretation
python main.py meeting.mp3 --template summary \
--focus architecture implementation timeline
python main.py meeting.mp3 --template summary --temperature 0.8
python main.py meeting.mp3 \
--template technical_specs \
--instruction "Focus on architecture decisions" \
--focus design patterns scalability \
--context "System design review" \
--temperature 0.4
python main.py board_meeting.mp3 --template summary \
--instruction "Create an executive summary" \
--focus strategy finance metrics
python main.py tech_review.mp3 --template technical_specs \
--focus architecture security performance
python main.py project_update.mp3 --musical-style hiphop \
--focus achievements milestones \
--context "Successful project completion"
-
API Key Error
Error: OPENAI_API_KEY environment variable is required
Solution: Check your .env file configuration
-
Template Not Found
Template 'xyz' not found. Using default template.
Solution: Check template name with --list-templates
-
Transcription Failed
Error during transcription
Solution: Verify audio file format and accessibility
-
Audio Quality
- Use clear audio recordings
- Minimize background noise
- Support common formats (mp3, wav, m4a)
-
Template Selection
- Use appropriate templates for content type
- Consider audience when choosing musical styles
- Match temperature to desired creativity level
-
System Resources
- Monitor API usage
- Consider file size limitations
- Check available disk space for templates
- Fork the repository
- Create your feature branch
- Add your templates to appropriate directories
- Submit a pull request
[Your License Here]
- OpenAI for Whisper and GPT APIs
- Contributors and template creators
- [Other acknowledgments]
Would you like me to expand any section or add more specific examples for certain use cases?