diff --git a/test/test_transforms.py b/test/test_transforms.py
index 8cca3085e0..3fe615437a 100644
--- a/test/test_transforms.py
+++ b/test/test_transforms.py
@@ -326,6 +326,18 @@ def test_scriptmodule_Resample(self):
 
         _test_script_module(transforms.Spectrogram, tensor, sample_rate, sample_rate_2)
 
+    def test_batch_Resample(self):
+        waveform = torch.randn(2, 2786)
+
+        # Single then transform then batch
+        expected = transforms.Resample()(waveform).repeat(3, 1, 1)
+
+        # Batch then transform
+        computed = transforms.Resample()(waveform.repeat(3, 1, 1))
+
+        self.assertTrue(computed.shape == expected.shape, (computed.shape, expected.shape))
+        self.assertTrue(torch.allclose(computed, expected))
+
     def test_scriptmodule_ComplexNorm(self):
         tensor = torch.rand((1, 2, 201, 2))
         _test_script_module(transforms.ComplexNorm, tensor)
diff --git a/torchaudio/transforms.py b/torchaudio/transforms.py
index 10390e6651..707252a9f3 100644
--- a/torchaudio/transforms.py
+++ b/torchaudio/transforms.py
@@ -445,7 +445,17 @@ def forward(self, waveform):
             torch.Tensor: Output signal of dimension (..., time)
         """
         if self.resampling_method == 'sinc_interpolation':
-            return kaldi.resample_waveform(waveform, self.orig_freq, self.new_freq)
+
+            # pack batch
+            shape = waveform.size()
+            waveform = waveform.view(-1, shape[-1])
+
+            waveform = kaldi.resample_waveform(waveform, self.orig_freq, self.new_freq)
+
+            # unpack batch
+            waveform = waveform.view(shape[:-1] + waveform.shape[-1:])
+
+            return waveform
 
         raise ValueError('Invalid resampling method: %s' % (self.resampling_method))