diff --git a/test/torchaudio_unittest/transforms/torchscript_consistency_impl.py b/test/torchaudio_unittest/transforms/torchscript_consistency_impl.py
index 506ca9af6c..5258343181 100644
--- a/test/torchaudio_unittest/transforms/torchscript_consistency_impl.py
+++ b/test/torchaudio_unittest/transforms/torchscript_consistency_impl.py
@@ -59,6 +59,10 @@ def test_AmplitudeToDB(self):
         spec = torch.rand((6, 201))
         self._assert_consistency(T.AmplitudeToDB(), spec)
 
+    def test_MelScale_invalid(self):
+        with self.assertRaises(ValueError):
+            torch.jit.script(T.MelScale())
+
     def test_MelScale(self):
         spec_f = torch.rand((1, 201, 6))
         self._assert_consistency(T.MelScale(n_stft=201), spec_f)
diff --git a/torchaudio/transforms.py b/torchaudio/transforms.py
index c7a72c55a7..930bd88a8f 100644
--- a/torchaudio/transforms.py
+++ b/torchaudio/transforms.py
@@ -284,6 +284,20 @@ def __init__(self,
             self.mel_scale)
         self.register_buffer('fb', fb)
 
+    def __prepare_scriptable__(self):
+        r"""If `self.fb` is empty, the `forward` method will try to resize the parameter,
+        which does not work once the transform is scripted. However, this error does not happen
+        until the transform is executed. This is inconvenient especially if the resulting
+        TorchScript object is executed in other environments. Therefore, we check the
+        validity of `self.fb` here and fail if the resulting TS does not work.
+
+        Returns:
+            MelScale: self
+        """
+        if self.fb.numel() == 0:
+            raise ValueError("n_stft must be provided at construction")
+        return self
+
     def forward(self, specgram: Tensor) -> Tensor:
         r"""
         Args: