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25d0747 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 | # EMOTIA Architecture
## System Overview
EMOTIA is a multi-modal AI system that analyzes video calls to infer emotional state, conversational intent, engagement, and confidence using facial expressions, vocal tone, spoken language, and temporal context.
## Architecture Diagram
```
┌─────────────────┐ ┌─────────────────┐ ┌─────────────────┐
│ Video Input │ │ Audio Input │ │ Text Input │
│ (25-30 FPS) │ │ (16kHz WAV) │ │ (ASR Trans.) │
└─────────────────┘ └─────────────────┘ └─────────────────┘
│ │ │
▼ ▼ ▼
┌─────────────────┐ ┌─────────────────┐ ┌─────────────────┐
│ Vision Branch │ │ Audio Branch │ │ Text Branch │
│ • ViT-Base │ │ • CNN + Trans. │ │ • BERT Encoder │
│ • Face Detect │ │ • Wav2Vec2 │ │ • Intent Detect │
│ • Emotion Class │ │ • Prosody │ │ • Sentiment │
└─────────────────┘ └─────────────────┘ └─────────────────┘
│ │ │
└────────────────────────┼────────────────────────┘
▼
┌─────────────────────────────┐
│ Cross-Modal Fusion │
│ • Attention Mechanism │
│ • Dynamic Weighting │
│ • Temporal Transformer │
│ • Modality Contributions │
└─────────────────────────────┘
│
▼
┌─────────────────────────────┐
│ Multi-Task Outputs │
│ • Emotion Classification │
│ • Intent Classification │
│ • Engagement Regression │
│ • Confidence Estimation │
└─────────────────────────────┘
```
## Component Details
### Vision Branch
- **Input**: RGB video frames (224x224)
- **Face Detection**: OpenCV Haar cascades
- **Feature Extraction**: Vision Transformer (ViT-Base)
- **Fine-tuning**: FER-2013, AffectNet, RAF-DB datasets
- **Output**: Emotion logits (7 classes), confidence score
### Audio Branch
- **Input**: Audio waveforms (16kHz, 3-second windows)
- **Preprocessing**: Mel-spectrogram extraction
- **Feature Extraction**: Wav2Vec2 + CNN layers
- **Prosody Analysis**: Pitch, rhythm, energy features
- **Output**: Emotion logits, stress/confidence score
### Text Branch
- **Input**: Transcribed speech text
- **Preprocessing**: Tokenization, cleaning
- **Feature Extraction**: BERT-base for intent/sentiment
- **Intent Detection**: Hesitation phrases, confidence markers
- **Output**: Intent logits (5 classes), sentiment logits
### Fusion Network
- **Modality Projection**: Linear layers to common embedding space (256D)
- **Cross-Attention**: Multi-head attention between modalities
- **Temporal Modeling**: Transformer encoder for sequence processing
- **Dynamic Weighting**: Learned modality importance scores
- **Outputs**: Fused predictions with contribution weights
## Data Flow
1. **Input Processing**: Video frames, audio chunks, ASR text
2. **Sliding Windows**: 5-10 second temporal windows
3. **Feature Extraction**: Parallel processing per modality
4. **Fusion**: Cross-modal attention and temporal aggregation
5. **Prediction**: Multi-task classification/regression
6. **Explainability**: Modality contribution scores
## Deployment Architecture
```
┌─────────────────────────────────────────────────────────────┐
│ Client Application │
│ ┌─────────────────────────────────────────────────────┐ │
│ │ WebRTC Video Stream │ │
│ │ • Camera Access │ │
│ │ • Audio Capture │ │
│ │ • Real-time Streaming │ │
│ └─────────────────────────────────────────────────────┘ │
└─────────────────────────────────────────────────────────────┘
│
▼
┌─────────────────────────────────────────────────────────────┐
│ FastAPI Backend │
│ ┌─────────────────────────────────────────────────────┐ │
│ │ Inference Pipeline │ │
│ │ • Model Loading │ │
│ │ • Preprocessing │ │
│ │ • GPU Inference │ │
│ │ • Post-processing │ │
│ └─────────────────────────────────────────────────────┘ │
│ ┌─────────────────────────────────────────────────────┐ │
│ │ Real-time Processing │ │
│ │ • Sliding Window Buffering │ │
│ │ • Asynchronous Processing │ │
│ │ • Streaming Responses │ │
│ └─────────────────────────────────────────────────────┘ │
└─────────────────────────────────────────────────────────────┘
│
▼
┌─────────────────────────────────────────────────────────────┐
│ Response Formatting │
│ • JSON API Responses │
│ • Real-time WebSocket Updates │
│ • Batch Processing for Post-call Analysis │
└─────────────────────────────────────────────────────────────┘
```
## Performance Requirements
- **Latency**: <200ms end-to-end
- **Throughput**: 25-30 FPS video processing
- **Accuracy**: F1 > 0.80 for emotion classification
- **Scalability**: Horizontal scaling with load balancer
- **Reliability**: 99.9% uptime, graceful degradation
## Security Considerations
- **Data Privacy**: No biometric storage by default
- **Encryption**: TLS 1.3 for all communications
- **Access Control**: API key authentication
- **Audit Logging**: All inference requests logged
- **Compliance**: GDPR, CCPA compliance features |