diff --git a/codes/models/asr/w2v_wrapper.py b/codes/models/asr/w2v_wrapper.py
index d5e694da..b5bf5737 100644
--- a/codes/models/asr/w2v_wrapper.py
+++ b/codes/models/asr/w2v_wrapper.py
@@ -20,7 +20,7 @@ class Wav2VecWrapper(nn.Module):
     """
     Basic wrapper class that makes Wav2Vec2 usable by DLAS.
     """
-    def __init__(self, vocab_size=148, basis_model='facebook/wav2vec2-large', freeze_transformer=False, output_wer=True, checkpointing_enabled=True, provide_attention_mask=False):
+    def __init__(self, vocab_size=148, basis_model='facebook/wav2vec2-large', freeze_transformer=False, output_wer=True, checkpointing_enabled=True, provide_attention_mask=False, spec_augment=True):
         super().__init__()
         self.provide_attention_mask = provide_attention_mask
         
@@ -31,7 +31,7 @@ class Wav2VecWrapper(nn.Module):
         self.w2v.config.vocab_size = vocab_size
         self.w2v.config.pad_token_id = 0
         self.w2v.config.ctc_loss_reduction = 'mean'
-        self.w2v.config.apply_spec_augment = True
+        self.w2v.config.apply_spec_augment = spec_augment
 
         # We always freeze the feature extractor, which needs some special operations in DLAS
         for p in self.w2v.wav2vec2.feature_extractor.parameters():