leave silence

app/main.py

@@ -190,9 +190,9 @@ label_encoder = joblib.load('app/1713661470.6730225_label_encoder.joblib')
 def preprocess_audio(audio_data, rate):
     audio_data = nr.reduce_noise(y=audio_data, sr=rate)
     # remove silence
-    intervals = librosa.effects.split(audio_data, top_db=20)
-    # Concatenate non-silent intervals
-    audio_data = np.concatenate([audio_data[start:end] for start, end in intervals])
+    # intervals = librosa.effects.split(audio_data, top_db=20)
+    # # Concatenate non-silent intervals
+    # audio_data = np.concatenate([audio_data[start:end] for start, end in intervals])
 
     audio_data = librosa.util.normalize(audio_data)
     audio_data, _ = librosa.effects.trim(audio_data)