AI Audio Annotation Platform
A platform accelerating audio data-labelling workflows: OpenAI models and PyAudio capture audio, generate transcriptions and help annotators produce structured annotations under strict validation rules. A companion browser extension auto-fills annotation fields on the DataForce TransPerfect site.
The challenge
Audio data labelling was slow: annotators listened to samples, described voice and speech characteristics by hand, and then re-entered the results into the client’s labelling platform, DataForce by TransPerfect, field by field.
What we did
Built an annotation platform with a Django backend and Next.js frontend. OpenAI models and PyAudio capture audio, generate transcriptions, and help annotators produce structured annotations under strict validation rules. A companion browser extension integrates with the DataForce site and fills the annotation fields automatically from the generated results.
The outcome
Less manual entry, more consistent annotations, and a labelling workflow that moves at the speed of review rather than transcription.
By the numbers
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Technology stack
Technologies that powered this project.
Frontend
Backend
Database & Tools
Development process
Our proven methodology for delivering exceptional results.
Discovery & Planning
Understanding requirements, analyzing scope, and creating a detailed roadmap
1-2 weeks
Design & Architecture
System architecture, UI/UX designs, and technical specifications
2-3 weeks
Development & Testing
Agile development with continuous testing, code reviews, and QA
4-8 weeks
Deployment & Launch
Production deployment, performance optimization, and go-live support
1 week
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