VoiceEmoji

Decode emotions through voice analysis with AI-powered insights

Emotion Recognition AI Visualization Speech Analysis

✨ Key Features

Multi-format Support

Process MP3, OGG, and WAV audio files with professional-grade analysis

Advanced Visualization

Interactive emotional maps using t-SNE, PCA, and UMAP projections

Real-time Analysis

10-second segment processing with dynamic emotion tracking

🔍 How It Works

System architecture diagram

1. Audio Segmentation

Divide input audio into 10-second segments for granular analysis

2. AI Processing

Whisper-large-v3 model for emotion recognition and BERT for text analysis

3. Visualization

Generate interactive psycho-emotional maps and temporal charts

Emotion Spectrum

Multidimensional mapping of vocal emotional signatures

t-SNE PCA

⚙️ Technical Stack

Core Models

  • Whisper-large-v3
  • BERT-base
  • UMAP

Libraries

  • Transformers
  • Librosa
  • Matplotlib

Infrastructure

  • Python 3.8
  • Tkinter GUI
  • Hugging Face Hub