diff --git a/audiomentations/augmentations/transforms.py b/audiomentations/augmentations/transforms.py
index 39a1ac77..c347375e 100644
--- a/audiomentations/augmentations/transforms.py
+++ b/audiomentations/augmentations/transforms.py
@@ -84,17 +84,19 @@ def apply(self, samples, sample_rate):
 class TimeMask(BasicTransform):
     """Mask some time band on the spectrogram. Inspired by https://arxiv.org/pdf/1904.08779.pdf """
 
-    def __init__(self, min_band_part=0.0, max_band_part=0.5, p=0.5):
+    def __init__(self, min_band_part=0.0, max_band_part=0.5, fade=False, p=0.5):
         """
         :param min_band_part: Minimum length of the silent part as a fraction of the
             total sound length. Float.
         :param max_band_part: Maximum length of the silent part as a fraction of the
             total sound length. Float.
+        :param fade: Bool, Add linear fade in and fade out of the silent part.
         :param p:
         """
         super().__init__(p)
         self.min_band_part = min_band_part
         self.max_band_part = max_band_part
+        self.fade = fade
 
     def apply(self, samples, sample_rate):
         new_samples = samples.copy()
@@ -103,7 +105,12 @@ def apply(self, samples, sample_rate):
             int(new_samples.shape[0] * self.max_band_part),
         )
         _t0 = random.randint(0, new_samples.shape[0] - _t)
-        new_samples[_t0 : _t0 + _t] = 0
+        mask = np.zeros(_t)
+        if self.fade:
+            fade_length = min(int(sample_rate * 0.01), int(_t * 0.1))
+            mask[0:fade_length] = np.linspace(1, 0, num=fade_length)
+            mask[-fade_length:] = np.linspace(0, 1, num=fade_length)
+        new_samples[_t0 : _t0 + _t] *= mask
         return new_samples
 
 
diff --git a/tests/test_time_mask.py b/tests/test_time_mask.py
index 009295db..2ac02cdc 100644
--- a/tests/test_time_mask.py
+++ b/tests/test_time_mask.py
@@ -20,3 +20,35 @@ def test_dynamic_length(self):
         std_in = np.mean(np.abs(samples_in))
         std_out = np.mean(np.abs(samples_out))
         self.assertLess(std_out, std_in)
+
+    def test_dynamic_length_with_fade(self):
+        sample_len = 1024
+        samples_in = np.random.normal(0, 1, size=sample_len).astype(np.float32)
+        sample_rate = 16000
+        augmenter = Compose(
+            [TimeMask(min_band_part=0.2, max_band_part=0.5, fade=True, p=1.0)]
+        )
+
+        samples_out = augmenter(samples=samples_in, sample_rate=sample_rate)
+        self.assertEqual(samples_out.dtype, np.float32)
+        self.assertEqual(len(samples_out), sample_len)
+
+        std_in = np.mean(np.abs(samples_in))
+        std_out = np.mean(np.abs(samples_out))
+        self.assertLess(std_out, std_in)
+
+    def test_dynamic_length_with_fade_short_signal(self):
+        sample_len = 100
+        samples_in = np.random.normal(0, 1, size=sample_len).astype(np.float32)
+        sample_rate = 16000
+        augmenter = Compose(
+            [TimeMask(min_band_part=0.2, max_band_part=0.5, fade=True, p=1.0)]
+        )
+
+        samples_out = augmenter(samples=samples_in, sample_rate=sample_rate)
+        self.assertEqual(samples_out.dtype, np.float32)
+        self.assertEqual(len(samples_out), sample_len)
+
+        std_in = np.mean(np.abs(samples_in))
+        std_out = np.mean(np.abs(samples_out))
+        self.assertLess(std_out, std_in)