diff --git a/se_extractor.py b/se_extractor.py
index 3ea2b9d..b916406 100644
--- a/se_extractor.py
+++ b/se_extractor.py
@@ -5,19 +5,21 @@ from glob import glob
 import numpy as np
 from pydub import AudioSegment
 from faster_whisper import WhisperModel
+import hashlib
+import base64
+import librosa
 from whisper_timestamped.transcribe import get_audio_tensor, get_vad_segments
 
 model_size = "medium"
 # Run on GPU with FP16
 model = None
-def split_audio_whisper(audio_path, target_dir='processed'):
+def split_audio_whisper(audio_path, target_dir, audio_name):
     global model
     if model is None:
         model = WhisperModel(model_size, device="cuda", compute_type="float16")
     audio = AudioSegment.from_file(audio_path)
     max_len = len(audio)
 
-    audio_name = os.path.basename(audio_path).rsplit('.', 1)[0]
     target_folder = os.path.join(target_dir, audio_name)
     
     segments, info = model.transcribe(audio_path, beam_size=5, word_timestamps=True)
@@ -69,7 +71,7 @@ def split_audio_whisper(audio_path, target_dir='processed'):
     return wavs_folder
 
 
-def split_audio_vad(audio_path, target_dir, split_seconds=10.0):
+def split_audio_vad(audio_path, target_dir, audio_name, split_seconds=10.0):
     SAMPLE_RATE = 16000
     audio_vad = get_audio_tensor(audio_path)
     segments = get_vad_segments(
@@ -90,7 +92,6 @@ def split_audio_vad(audio_path, target_dir, split_seconds=10.0):
     
     audio_dur = audio_active.duration_seconds
     print(f'after vad: dur = {audio_dur}')
-    audio_name = os.path.basename(audio_path).rsplit('.', 1)[0]
     target_folder = os.path.join(target_dir, audio_name)
     wavs_folder = os.path.join(target_folder, 'wavs')
     os.makedirs(wavs_folder, exist_ok=True)
@@ -112,13 +113,18 @@ def split_audio_vad(audio_path, target_dir, split_seconds=10.0):
     return wavs_folder
 
 
-    
+def hash_numpy_array(array):
+    array_bytes = array.tobytes()
+    hash_object = hashlib.sha256(array_bytes)
+    hash_value = hash_object.digest()
+    base64_value = base64.b64encode(hash_value)
+    return base64_value.decode('utf-8')[:16].replace('/', '&')    
 
 
 def get_se(audio_path, vc_model, target_dir='processed', vad=True):
     device = vc_model.device
-
-    audio_name = os.path.basename(audio_path).rsplit('.', 1)[0]
+    audio_hash = hash_numpy_array(librosa.load(audio_path, mono=True)[0])
+    audio_name = os.path.basename(audio_path).rsplit('.', 1)[0] + '_' + audio_hash
     se_path = os.path.join(target_dir, audio_name, 'se.pth')
 
     if os.path.isfile(se_path):
@@ -127,9 +133,9 @@ def get_se(audio_path, vc_model, target_dir='processed', vad=True):
     if os.path.isdir(audio_path):
         wavs_folder = audio_path
     elif vad:
-        wavs_folder = split_audio_vad(audio_path, target_dir)
+        wavs_folder = split_audio_vad(audio_path, target_dir, audio_name)
     else:
-        wavs_folder = split_audio_whisper(audio_path, target_dir)
+        wavs_folder = split_audio_whisper(audio_path, target_dir, audio_name)
     
     audio_segs = glob(f'{wavs_folder}/*.wav')
     if len(audio_segs) == 0: