diff --git a/codes/data/audio/wav_aug.py b/codes/data/audio/wav_aug.py
index a35646d0..74723a44 100644
--- a/codes/data/audio/wav_aug.py
+++ b/codes/data/audio/wav_aug.py
@@ -23,7 +23,9 @@ class WavAugmentor:
         pass
 
     def augment(self, wav, sample_rate):
-        speed_effect = ['speed', rdstr(.7, 1)]
+        speed_effect = ['speed', rdstr(.8, 1)]
+        '''
+        Band effects are disabled until I can audit them better.
         band_effects = [
             ['reverb', '-w'],
             ['reverb'],
@@ -39,15 +41,16 @@ class WavAugmentor:
             ['sinc', '3k-4k']
         ]
         band_effect = random.choice(band_effects)
+        '''
         volume_effects = [
             ['loudness', rdi(10,-2)],
             ['overdrive', rdi(20,0), rdi(20,0)],
         ]
         vol_effect = random.choice(volume_effects)
-        effects = [speed_effect, band_effect, vol_effect]
+        effects = [speed_effect, vol_effect]
         out, sr = torchaudio.sox_effects.apply_effects_tensor(wav, sample_rate, effects)
         # Add a variable amount of noise
-        out = out + torch.rand_like(out) * random.random() * .05
+        out = out + torch.rand_like(out) * random.random() * .03
         return out
 
 
diff --git a/codes/scripts/audio/test_audio_gen.py b/codes/scripts/audio/test_audio_gen.py
index ce441c11..fd3c97f8 100644
--- a/codes/scripts/audio/test_audio_gen.py
+++ b/codes/scripts/audio/test_audio_gen.py
@@ -51,7 +51,7 @@ if __name__ == "__main__":
     torch.backends.cudnn.benchmark = True
     want_metrics = False
     parser = argparse.ArgumentParser()
-    parser.add_argument('-opt', type=str, help='Path to options YAML file.', default='../options/test_vqvae_audio_lj.yml')
+    parser.add_argument('-opt', type=str, help='Path to options YAML file.', default='../options/test_gpt_tts_lj.yml')
     opt = option.parse(parser.parse_args().opt, is_train=False)
     opt = option.dict_to_nonedict(opt)
     utils.util.loaded_options = opt
diff --git a/codes/scripts/audio/test_audio_similarity.py b/codes/scripts/audio/test_audio_similarity.py
index 34d6fb3d..2ffaeb3d 100644
--- a/codes/scripts/audio/test_audio_similarity.py
+++ b/codes/scripts/audio/test_audio_similarity.py
@@ -20,12 +20,13 @@ if __name__ == '__main__':
             clip = clip[:,0]
         clip = clip[:window].unsqueeze(0)
         clip = clip / 32768.0  # Normalize
+        clip = clip + torch.rand_like(clip) * .03  # Noise (this is how the model was trained)
         assert sr == 24000
         clips.append(clip)
     clips = torch.stack(clips, dim=0)
 
     resnet = resnet34()
-    sd = torch.load('../experiments/train_byol_audio_clips/models/66000_generator.pth')
+    sd = torch.load('../experiments/train_byol_audio_clips/models/57000_generator.pth')
     sd = extract_byol_model_from_state_dict(sd)
     resnet.load_state_dict(sd)
     embedding = resnet(clips, return_pool=True)