Update ldq_perceptual_layer.py

ldq_perceptual_layer.py

@@ -17,45 +17,47 @@ def apply_perceptual_mixing(audio: np.ndarray, features: Dict[str, Any], sr: int
     if audio.ndim == 1:
         audio = audio[:, np.newaxis]
     
-    # 1. Multiband saturation based on contrast
+    # 1. Multiband saturation based on contrast (reduced for less buzz)
     contrast = features.get("contrast", 0.15)
-    sat_amount = contrast * 3.0  # 0.0 to ~1.0
+    sat_amount = contrast * 1.5  # Reduced from 3.0
     
-    # Simple harmonic distortion
+    # Soft saturation
     if sat_amount > 0:
-        audio = np.tanh(audio * (1 + sat_amount)) / np.tanh(1 + sat_amount)
+        audio = np.tanh(audio * (1 + sat_amount * 0.5)) / np.tanh(1 + sat_amount * 0.5)
     
     # 2. Sidechain compression based on hue
     hue = features.get("average_hue", 180)
     # Redder hue = faster release
     release_time = 0.1 + (hue / 360) * 0.3  # 0.1-0.4 seconds
     
-    # Simulate sidechain by reducing gain during kick
-    # For now, simple gain reduction based on edge density
+    # Gentle gain reduction based on edge density
     edge_density = features.get("edge_density", 0.02)
-    reduction = 1.0 - (edge_density * 2.0)
-    reduction = max(0.6, reduction)
+    reduction = 1.0 - (edge_density * 1.0)  # Less reduction
+    reduction = max(0.7, reduction)
     audio *= reduction
     
     # 3. Stereo width based on keypoint distribution
     chaos = features.get("chaos_keypoints", 0)
-    width = 1.0 + (chaos / 1000) * 0.5
+    width = 1.0 + (chaos / 1000) * 0.3  # Less width
     if audio.shape[1] == 2:
         mid = (audio[:, 0] + audio[:, 1]) / 2
         side = (audio[:, 0] - audio[:, 1]) / 2
         audio[:, 0] = mid + side * width
         audio[:, 1] = mid - side * width
     
-    # 4. Reverb based on color variance
+    # 4. Reverb based on color variance (reduced)
     colorfulness = features.get("colorfulness", 0.1)
-    reverb_decay = 0.5 + colorfulness * 5.0  # 0.5-5.5 seconds
+    reverb_decay = 0.3 + colorfulness * 3.0  # 0.3-3.3 seconds (shorter)
     
-    # Simple reverb simulation (delay line)
-    if reverb_decay > 1.0:
-        delay_samples = int(sr * 0.05)  # 50ms
+    if reverb_decay > 0.8:
+        delay_samples = int(sr * 0.03)  # 30ms (shorter)
         if len(audio) > delay_samples:
             reverb = np.roll(audio, delay_samples, axis=0)
-            reverb *= 0.3
-            audio += reverb * min(1.0, reverb_decay / 3.0)
+            reverb *= 0.2  # Less reverb
+            audio += reverb * min(0.6, reverb_decay / 4.0)
+    
+    # 5. Gentle EQ: cut above 5 kHz to reduce buzz
+    sos = signal.butter(2, 5000, btype='low', fs=sr, output='sos')
+    audio = signal.sosfilt(sos, audio, axis=0)
     
     return audio