Audio Communication Grading
Impact80% time saved
Time Saved80%
Consistency100%
FeedbackReal-time
Overview
Developed an automated audio grading system that evaluates students' verbal communication through multiple dimensions including pronunciation, fluency, grammar, and coherence. The system provides instant feedback and improvement suggestions.
The Challenge
Manual grading of audio submissions was time-consuming and inconsistent across different evaluators.
The Solution
Created a multi-model approach using speech-to-text, NLP analysis, and AI-powered feedback generation. Deployed on Linode for testing and AKS for production with full CI/CD automation.
Key Results
Automated grading of audio submissions
Consistent evaluation across all submissions
Real-time feedback generation
Tech Stack
Google Speech-to-TextIBM WatsonOpenAI WhisperFastAPILinodeAzure Kubernetes Service