Audio Analysis Pipeline
A comprehensive serverless audio processing solution called "Distiller" that transforms spoken content into structured, analyzed data using AWS cloud services and advanced NLP techniques.
Key Features
- Serverless Architecture: Built on AWS Lambda and Step Functions for scalable, on-demand processing
- Semantic Chunking: Intelligent segmentation of audio content based on semantic meaning
- Recursive Analysis: Multi-level processing of audio content to extract deeper insights
- Advanced NLP Capabilities:
- Sentiment analysis using AWS Comprehend
- AI-powered summarization using Claude via AWS Bedrock
- Entity recognition and relationship mapping
CLI Tool
The project includes a companion command-line interface in Rust that provides:
- Seamless AWS Service Interactions: Simplified management of complex AWS service integrations
- File Upload Management: Efficient handling of audio file uploads to the processing pipeline
- Pipeline Execution Control: Start, monitor, and manage audio processing jobs
- Error Handling: Robust error recovery and reporting
- Progress Tracking: Real-time visibility into processing status
Technical Stack
- Cloud Services: AWS Lambda, Step Functions, Bedrock, Comprehend
- Languages: Rust (CLI), Python (Lambda functions)
- AI Models: Claude (for summarization)
- Repository: github.com/dbolivar25/distiller
The solution implements a cloud-native architecture with advanced AI/ML capabilities while providing straightforward interfaces for developers.