further fine grained s-curve control

app.py

@@ -217,32 +217,35 @@ def generate(audio_path, ins, speed, alpha, beta, embedding, steps=200):
         # Post-Processing
         thresh = np.percentile(np.abs(synthaud), 95)
         CUT_SAMPLES = 20000  # max samples to cut, in practice only 4-6k are actually cut
+        lead_percent = 0.008
+        trail_percent = 0.009
+
 
         # Leading artefact removal
-        left = CUT_SAMPLES + 1000
+        left = CUT_SAMPLES + int(len(synthaud) * lead_percent)
         for j in range(left):
             if abs(synthaud[j]) > thresh:
                 left = j
                 break
             
-        left = max(0, min(left - 1000, CUT_SAMPLES))
+        left = max(0, min(left - int(len(synthaud) * lead_percent), CUT_SAMPLES))
         synthaud[:left] = 0
-        for k in range(1000):
-            s = s_curve(k / 1000)
+        for k in range(int(len(synthaud) * lead_percent)):
+            s = s_curve(k / int(len(synthaud) * lead_percent))
             synthaud[k + left] *= s
 
         # Trailing artefact removal
-        right = len(synthaud) - CUT_SAMPLES - 1000
+        right = len(synthaud) - CUT_SAMPLES - int(len(synthaud) * trail_percent)
         for j in range(len(synthaud) - 1, right, -1):
             if abs(synthaud[j]) > thresh:
                 right = j
                 break
 
-        right = min(len(synthaud), max(right + 1000, len(synthaud) - CUT_SAMPLES))
+        right = min(len(synthaud), max(right + int(len(synthaud) * trail_percent), len(synthaud) - CUT_SAMPLES))
         synthaud[right:] = 0
-        for k in range(1000):
-            s = s_curve(k / 1000)
-            synthaud[right - 1000 + k] *= s
+        for k in range(int(len(synthaud) * trail_percent)):
+            s = s_curve(k / int(len(synthaud) * trail_percent))
+            synthaud[right - int(len(synthaud) * trail_percent) + k] *= s
 
 
         audio = np.concatenate((audio, synthaud))