remove leading silence

app.py

@@ -6,6 +6,18 @@ from audio_recorder_streamlit import audio_recorder
 
 import pedalboard as pb
 
+@st.cache
+def remove_leading_silence(wave, threshold=0.001):
+    clean = np.array([])
+    for i, samples in enumerate(wave):
+        if abs(samples[0]) > threshold or abs(samples[1]) > threshold:
+            clean = wave[i:]
+            break
+    if clean.any():
+        return clean
+    else:
+        return wave
+
 st.title("👹 Voice Refuckulator")
 
 audio_bytes = audio_recorder()
@@ -14,13 +26,17 @@ board = pb.Pedalboard([pb.Reverb(room_size=0.100), pb.Gain(-10)])
 if audio_bytes:
     # data must be transposed, maybe before processing?
     wave, sr = sf.read(io.BytesIO(audio_bytes))
-    effected = board(wave, sr, reset=False)
+    wave = remove_leading_silence(wave)
+    try:
+        effected = board(wave, sr, reset=False)
+    except:
+        effected = wave
     cols = st.columns(5)
-    stretch_factor = cols[0].slider("🧌 Trollizer", 1, 32, 16)
-    chunk_factor = cols[1].slider("🕋 Chunkinator", 1, 16, 8)
-    chunk_dividend = cols[2].slider("🫀 Dechunkizer", 1, 32, 16)
-    shuffle = cols[3].slider("🤡 Impredictidiblize", 1, 32, 16)
-    sr_factor = cols[4].slider("🏃‍♀️ Chirpidize", 1, 16, 8)
+    stretch_factor = cols[0].slider("🧌 Trollizer", 1, 32, 1)
+    chunk_factor = cols[1].slider("🕋 Chunkinator", 1, 16, 1)
+    chunk_dividend = cols[2].slider("🫀 Dechunkizer", 1, 32, 1)
+    shuffle = cols[3].slider("🤡 Impredictidiblize", 1, 32, 1)
+    sr_factor = cols[4].slider("🏃‍♀️ Chirpidize", 1, 16, 1)
     stretched = []
     for chunk in np.array_split(effected, chunk_dividend):
         for i in range(chunk_factor):