A deep learning system that detects student emotional states from facial, speech, and text signals.
Facial emotion is classified from webcam input, speech emotion is extracted from pitch, tone and intensity, and written responses are scored through NLP sentiment analysis. All three modalities are fused into a single, more reliable prediction of the student's emotional state.
Any single emotion signal is unreliable — a neutral face hides frustration, and text alone misses tone. In online learning, disengagement goes unnoticed until results drop.
Read all three channels simultaneously and fuse them, so agreement across modalities raises confidence and disagreement is handled explicitly rather than silently.
Facial Emotion Recognition
Deep learning image classification from webcam input.
Speech Emotion Recognition
Extracts pitch, tone, and intensity from audio.
Text Emotion Analysis
NLP-based sentiment detection from written responses.
Multimodal Fusion
Combines all three modalities into a single, more reliable prediction.
Vision
Audio
NLP
Fusion
Multimodal capture
Webcam, microphone and text responses are collected.
Per-modality scoring
Each channel produces an independent emotion estimate.
Fusion
Estimates are combined into a single prediction.
Reporting
Emotional state is surfaced for the instructor.
Every project is quoted individually, because the price depends on the modules you need, your technology stack, your college's format and your deadline. Send us the project name on WhatsApp and we'll share a quote the same day.
Yes. Share your guide's requirements, preferred technology stack and abstract format, and we adapt the modules, dataset or UI accordingly.
That is the point of the explanation session. We walk you through the architecture, every module, the flow of data and the results, and hand over a viva question bank with answers.
We help you with setup end to end — dependencies, environment, database and configuration — over chat or a call until it runs on your machine.
Yes. Post-delivery support is included, so you can come back for fixes, doubts or demo help even after the project is delivered.
Get complete source code, documentation, PPT, explanation, and support.
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