diff --git a/pipeline/feature_extractors.py b/pipeline/feature_extractors.py
index 45224fb..cf9dbdb 100644
--- a/pipeline/feature_extractors.py
+++ b/pipeline/feature_extractors.py
@@ -214,21 +214,31 @@ class LoudAudioFeatureExtractor(FeatureExtractor):
         OUTPUT_DIR = "/tmp"
         return f"{OUTPUT_DIR}/{os.path.basename(path)}.wav"
 
+    def _get_loudnesses(self, data, meter, rate, window_size, stride_size):
+        """Extract loudnesses from the audio data using pyloudnorm
+
+        return a list of 2-tuples, each representing a timecode and loudness value
+        """
+        loudnesses = []
+
+        for w in range(0, len(data)-window_size, stride_size):
+            window = data[w:w+window_size, 0:2] # extract window
+            loudnesses.append( (w/rate, meter.integrated_loudness(window)) )
+
+        return loudnesses
+
     def _loudnorm(self, audio_file):
         """Run pyloudnorm on the audio file"""
         data, rate = soundfile.read(audio_file) # load audio (with shape (samples, channels))
         meter = pyloudnorm.Meter(rate=rate,block_size=0.3) # create BS.1770 meter
 
-        loudnesses = []
         loudness_features = []
         window_size = int(rate * 0.5) # 500ms
         stride_size = int(rate * 0.5) # 500ms -- no overlap
 
         # for w in range(data.shape[0]//100):
         #     loudnesses.append(meter.integrated_loudness(data[w:w+int(0.3*rate),0:2]))
-        for w in range(0, len(data)-window_size, stride_size):
-            window = data[w:w+window_size, 0:2] # extract window
-            loudnesses.append( (w/rate, meter.integrated_loudness(window)) )
+        loudnesses = self._get_loudnesses(data, meter, rate, window_size, stride_size)
 
         for timecode, loudval in sorted([l for l in loudnesses if float(l[1]) != float("-inf")], key=lambda x: x[1], reverse=True):
             # print(f"Timecode: {timecode}, Loudness: {loudval}")