diff --git a/pipeline/feature_extractors.py b/pipeline/feature_extractors.py
index 3706223..f9ab1ad 100644
--- a/pipeline/feature_extractors.py
+++ b/pipeline/feature_extractors.py
@@ -1,9 +1,13 @@
 from abc import ABC
 import logging
+import os
 import random
 import subprocess
 from ast import literal_eval
 from pipeline.utils import SourceMedia, Feature, Interval
+# for loudness detection
+import soundfile
+import pyloudnorm
 
 logger = logging.getLogger(__name__)
 
@@ -175,6 +179,68 @@ class LoudAudioFeatureExtractor(FeatureExtractor):
 
      teardown() is used to clean up temporary files created during setup (if specified by config)
     """
+    def __init__(self, input_files=None, config=None):
+        if not input_files:
+            raise ValueError("No input files provided!")
+        self.input_files = input_files
+        self.config = config
+        self.features = []
+
+    def _audio_file_from_path(self, path: str) -> str:
+        """Return the audio file path given a video file path
+
+        Example:
+          - in = "/path/to/video.mp4"
+          - out = "/tmp/video.mp4.wav"
+        """
+        OUTPUT_DIR = "/tmp"
+        return f"{OUTPUT_DIR}/{os.path.basename(path)}.wav"
+
+    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)) )
+
+        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}")
+            loudness_features.append((timecode, round(loudval, 3))) # round to 3 DP
+
+        return loudness_features
+
+    def setup(self):
+        """extract audio from video files to be processed by pyloudnorm
+
+        TODO: config -- hardcoded for now
+        """
+        # pyloudnorm expects WAV files
+        for file in self.input_files:
+            audio_file = self._audio_file_from_path(file.path)
+            # ffmpeg -i input.mp4 -vn -acodec pcm_s16le output.wav
+            subprocess.run(["ffmpeg", "-y", "-i", file.path, "-vn", "-acodec", "pcm_s16le", audio_file],
+                           stdout=subprocess.PIPE, stderr=subprocess.PIPE)
+
+    def run(self):
+        """Use pyloudnorm to detect loud audio"""
+        for file in self.input_files:
+            audio_file = self._audio_file_from_path(file.path)
+            loudnesses = self._loudnorm(audio_file)
+            for time, loudness in loudnesses:
+                self.features.append(Feature(interval=Interval(start=time, duration=0.500),
+                                             source=file, feature_extractor="loudness",
+                                             score=loudness))
+
+
 class VideoActivityFeatureExtractor(FeatureExtractor):
     """Feature extractor for video activity detection.