diff --git a/codes/scripts/audio/preparation/spleeter_dataset.py b/codes/scripts/audio/preparation/spleeter_dataset.py
index a0a198fc..c840e4f9 100644
--- a/codes/scripts/audio/preparation/spleeter_dataset.py
+++ b/codes/scripts/audio/preparation/spleeter_dataset.py
@@ -7,8 +7,10 @@ from data.util import find_audio_files
 
 
 class SpleeterDataset(Dataset):
-    def __init__(self, src_dir, sample_rate=22050, max_duration=20):
+    def __init__(self, src_dir, sample_rate=22050, max_duration=20, skip=0):
         self.files = find_audio_files(src_dir, include_nonwav=True)
+        if skip > 0:
+            self.files = self.files[skip:]
         self.audio_loader = AudioAdapter.default()
         self.sample_rate = sample_rate
         self.max_duration = max_duration
diff --git a/codes/scripts/audio/preparation/spleeter_split_voice_and_background_2.py b/codes/scripts/audio/preparation/spleeter_split_voice_and_background_2.py
index 0166aebd..5edf0b01 100644
--- a/codes/scripts/audio/preparation/spleeter_split_voice_and_background_2.py
+++ b/codes/scripts/audio/preparation/spleeter_split_voice_and_background_2.py
@@ -17,11 +17,9 @@ def main():
     output_sample_rate=22050
     batch_size=16
 
-    dl = DataLoader(SpleeterDataset(src_dir, output_sample_rate), batch_size=batch_size, shuffle=False, num_workers=1, pin_memory=True)
+    dl = DataLoader(SpleeterDataset(src_dir, output_sample_rate, skip=batch_size*33000), batch_size=batch_size, shuffle=False, num_workers=1, pin_memory=True)
     separator = Separator('pretrained_models/2stems', input_sr=output_sample_rate)
-    for e, batch in enumerate(tqdm(dl)):
-        #if e < 406500:
-        #    continue
+    for batch in tqdm(dl):
         waves = batch['wave']
         paths = batch['path']
         durations = batch['duration']