AudioProof: Audio-to-Text Verification
Automated verification system comparing Danish audio recordings against PDF documents using AI-powered transcription and custom comparison engine.
The Challenge
A European startup needed an efficient way to verify that audio recordings accurately reflected the text in PDF documents, particularly in the Danish language. Manual verification was time-consuming and error-prone, requiring a scalable automated solution.
Our Approach
We built an end-to-end verification pipeline combining AI transcription with intelligent text comparison.
Audio-to-Text Conversion
Google Speech-to-Text API transcribes Danish audio with high accuracy. GPT-4 further refines the transcription, handling language-specific nuances and improving output quality.
PDF Parsing
A proprietary algorithm extracts text from PDF documents, handling complexities such as page breaks, formatting, and punctuation. The algorithm normalizes text into a comparison-ready format.
Comparison Engine
A custom comparison engine identifies discrepancies between the audio transcription and PDF text — highlighting missing words, extra content, and deviations. Results are output as a marked-up PDF with highlighted differences.
API & Frontend
The backend is exposed via RESTful API for programmatic integration. A React frontend enables non-technical users to upload audio and PDF files, track processing, and view results in real time.
Technical Stack
- AI: Google Speech-to-Text, GPT-4
- Backend: Python, RESTful APIs
- Frontend: React
- Cloud: AWS
Results
- Automated content verification reducing manual review time
- High-accuracy Danish language transcription
- Visual diff output highlighting discrepancies between audio and text
- Scalable API-first architecture for integration with existing workflows