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Speech Emotion Detector

An AI-driven application that analyzes voice input to detect emotional states. Features real-time processing, emotion classification, and a dashboard for analytics visualization.

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Overview

An AI-driven application that analyzes voice input to detect emotional states. Features real-time processing, emotion classification, and a dashboard for analytics visualization.

Problem Statement

Understanding emotional context in voice communication requires specialized tools beyond text analysis.

Features

  • Real-time voice analysis
  • Multi-emotion detection
  • AI/ML processing pipeline
  • Analytics dashboard
  • Audio waveform visualization

Architecture

Python ML backend for emotion classification, React frontend for visualization, REST API communication layer.

Technologies Used

PythonJavaScriptAI/MLReactTensorFlow

Challenges

  • • Model accuracy optimization
  • • Real-time audio processing latency

Learnings

  • • Integrating ML models into web apps
  • • Audio processing fundamentals