Upload fusion_engine.py

src/models/fusion_engine.py

@@ -75,15 +75,15 @@ class LateDecisionFusion:
             color_code = "green"
             action_summary = "No significant psychological stress detected. Emotional tone is balanced."
         elif combined_stress_score < 55.0:
-            risk_tier = "Mild Stress"
+            risk_tier = f"Mild {final_category}" if final_category not in ["Normal", "Stress", "Calm / Normal"] else "Mild Stress"
             color_code = "blue"
             action_summary = f"Mild symptoms of {final_category.lower()} observed. Recommended: short breaks and time-management strategies."
         elif combined_stress_score < 80.0:
-            risk_tier = "Moderate / High Stress"
+            risk_tier = f"Moderate {final_category}" if final_category not in ["Normal", "Stress", "Calm / Normal"] else "Moderate Stress"
             color_code = "orange"
             action_summary = f"Significant signs of {final_category.lower()} and vocal tension detected. Recommended: structured counseling or grounding CBT exercises."
         else:
-            risk_tier = "Severe Emotional Distress / Risk"
+            risk_tier = f"Severe {final_category}" if final_category not in ["Normal", "Stress", "Calm / Normal"] else "Severe Stress"
             color_code = "red"
             action_summary = f"High emotional distress and acute {final_category.lower()} detected across both speech and text modalities. Immediate psychological check-in and support advised."
             
@@ -108,11 +108,14 @@ class LateDecisionFusion:
         if score < 30.0:
             tier, color, summary = "Minimal / Normal", "green", "No significant text stress markers identified."
         elif score < 55.0:
-            tier, color, summary = "Mild Stress", "blue", f"Mild linguistic markers of {cat.lower()} identified."
+            tier = f"Mild {cat}" if cat not in ["Normal", "Stress", "Calm / Normal"] else "Mild Stress"
+            color, summary = "blue", f"Mild linguistic markers of {cat.lower()} identified."
         elif score < 80.0:
-            tier, color, summary = "Moderate / High Stress", "orange", f"High frequency of {cat.lower()} vocabulary identified."
+            tier = f"Moderate {cat}" if cat not in ["Normal", "Stress", "Calm / Normal"] else "Moderate Stress"
+            color, summary = "orange", f"High frequency of {cat.lower()} vocabulary identified."
         else:
-            tier, color, summary = "Severe Emotional Distress / Risk", "red", f"Critical linguistic stress markers for {cat.lower()} detected."
+            tier = f"Severe {cat}" if cat not in ["Normal", "Stress", "Calm / Normal"] else "Severe Stress"
+            color, summary = "red", f"Critical linguistic stress markers for {cat.lower()} detected."
             
         return {
             "modality_status": "Single-Modality (Text Only)",
@@ -135,9 +138,9 @@ class LateDecisionFusion:
         elif score < 55.0:
             tier, color, summary = "Mild Stress", "blue", f"Slight vocal tension ({emotion.lower()}) observed."
         elif score < 80.0:
-            tier, color, summary = "Moderate / High Stress", "orange", f"High vocal agitation ({emotion.lower()}) and spectral energy detected."
+            tier, color, summary = "Moderate Stress", "orange", f"High vocal agitation ({emotion.lower()}) and spectral energy detected."
         else:
-            tier, color, summary = "Severe Emotional Distress / Risk", "red", f"Severe acoustic stress and emotional agitation ({emotion.lower()}) recorded."
+            tier, color, summary = "Severe Stress", "red", f"Severe acoustic stress and emotional agitation ({emotion.lower()}) recorded."
             
         return {
             "modality_status": "Single-Modality (Speech Only)",