Analysis Results

Emotion analysis for: {{ filename }}

Predicted Emotion

{% set emotion_icons = { 'angry': 'fas fa-angry text-danger', 'disgust': 'fas fa-frown text-secondary', 'fear': 'fas fa-scared text-warning', 'happy': 'fas fa-smile text-success', 'neutral': 'fas fa-meh text-info', 'sad': 'fas fa-sad-tear text-primary', 'surprise': 'fas fa-surprise text-warning' } %}

{{ emotion }}

{{ "%.1f"|format(confidence_scores[emotion] * 100) }}% Confidence
Confidence Scores by Emotion
{% for emotion, score in confidence_scores.items() %}
{{ emotion }} {{ "%.1f"|format(score * 100) }}%
{% endfor %}
Distribution Chart
Analysis Details
Top 3 Emotions:
    {% set emotions_list = confidence_scores.items()|list %} {% for emotion, score in emotions_list[:3] %}
  1. {{ emotion }}
    {{ "%.1f"|format(score * 100) }}%
  2. {% endfor %}
Analysis Info:
  • File: {{ filename }}
  • Model: CNN-based Deep Learning
  • Features: MFCC + Mel Spectrogram
  • Processing: Real-time
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