MentorMindAI is an AI-powered backend system that evaluates teaching quality from recorded videos and converts educational content into accessible learning formats.
The platform uses ONNX-based machine learning models, FastAPI, and asynchronous processing to provide scalable, reproducible, and fair video evaluations.
- Problem Statement
- Solution Overview
- Key Features
- Accessibility Modes
- System Architecture
- Project Structure
- Technology Stack
- Installation and Setup
- Running the Application
- API Endpoints
- Screenshots
- Contributors
- Future Scope
- License
Teaching quality evaluation is often subjective and inconsistent. Additionally, standard video-based learning is not accessible to learners with visual, hearing, or cognitive challenges.
There is a need for:
- Objective teaching quality assessment
- Automated feedback for mentors
- Inclusive and accessible learning formats
MentorMindAI provides:
- AI-based scoring of teaching videos
- Deterministic and reproducible evaluation metrics
- Automatic conversion of videos into accessible modes
Each uploaded teaching video is evaluated using ONNX models across the following dimensions:
- Clarity
- Engagement
- Pace
- Filler Word Usage
- Technical Depth
- Weighted Overall Score
Each metric is processed independently to ensure fairness and transparency.
Generates audio narration describing both visual and spoken content.
Automatically generates subtitles using Whisper Speech-to-Text and exports .srt files.
Produces simplified narration using text summarization and text-to-speech for better comprehension.