diff --git a/docs/source/functional.rst b/docs/source/functional.rst
index 5f68666539..da5cae0516 100644
--- a/docs/source/functional.rst
+++ b/docs/source/functional.rst
@@ -113,6 +113,11 @@ Functions to perform common audio operations.
 
 .. autofunction:: treble_biquad
 
+:hidden:`bass_biquad`
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+.. autofunction:: bass_biquad
+
 :hidden:`deemph_biquad`
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 
diff --git a/test/test_sox_compatibility.py b/test/test_sox_compatibility.py
index 2c8394ff45..5239f56ae8 100644
--- a/test/test_sox_compatibility.py
+++ b/test/test_sox_compatibility.py
@@ -265,6 +265,28 @@ def test_treble(self):
 
         self.assertEqual(output_waveform, sox_output_waveform, atol=1e-4, rtol=1e-5)
 
+    @unittest.skipIf("sox" not in BACKENDS, "sox not available")
+    @AudioBackendScope("sox")
+    def test_bass(self):
+        """
+        Test biquad bass filter, compare to SoX implementation
+        """
+
+        central_freq = 1000
+        q = 0.707
+        gain = 40
+
+        noise_filepath = common_utils.get_asset_path('whitenoise.wav')
+        E = torchaudio.sox_effects.SoxEffectsChain()
+        E.set_input_file(noise_filepath)
+        E.append_effect_to_chain("bass", [gain, central_freq, str(q) + 'q'])
+        sox_output_waveform, sr = E.sox_build_flow_effects()
+
+        waveform, sample_rate = torchaudio.load(noise_filepath, normalization=True)
+        output_waveform = F.bass_biquad(waveform, sample_rate, gain, central_freq, q)
+
+        self.assertEqual(output_waveform, sox_output_waveform, atol=1.5e-4, rtol=1e-5)
+
     @unittest.skipIf("sox" not in BACKENDS, "sox not available")
     @AudioBackendScope("sox")
     def test_deemph(self):
diff --git a/test/torchscript_consistency_impl.py b/test/torchscript_consistency_impl.py
index 4ee9149843..b8967be41a 100644
--- a/test/torchscript_consistency_impl.py
+++ b/test/torchscript_consistency_impl.py
@@ -367,6 +367,21 @@ def func(tensor):
 
         self._assert_consistency(func, waveform)
 
+    def test_bass(self):
+        if self.dtype == torch.float64:
+            raise unittest.SkipTest("This test is known to fail for float64")
+
+        waveform = common_utils.get_whitenoise(sample_rate=44100)
+
+        def func(tensor):
+            sample_rate = 44100
+            gain = 40.
+            central_freq = 1000.
+            q = 0.707
+            return F.bass_biquad(tensor, sample_rate, gain, central_freq, q)
+
+        self._assert_consistency(func, waveform)
+
     def test_deemph(self):
         if self.dtype == torch.float64:
             raise unittest.SkipTest("This test is known to fail for float64")
diff --git a/torchaudio/functional.py b/torchaudio/functional.py
index 94ff81526a..8491e6dafc 100644
--- a/torchaudio/functional.py
+++ b/torchaudio/functional.py
@@ -29,6 +29,7 @@
     "equalizer_biquad",
     "band_biquad",
     "treble_biquad",
+    "bass_biquad",
     "deemph_biquad",
     "riaa_biquad",
     "biquad",
@@ -983,6 +984,47 @@ def treble_biquad(
     return biquad(waveform, b0, b1, b2, a0, a1, a2)
 
 
+def bass_biquad(
+        waveform: Tensor,
+        sample_rate: int,
+        gain: float,
+        central_freq: float = 100,
+        Q: float = 0.707
+) -> Tensor:
+    r"""Design a bass tone-control effect.  Similar to SoX implementation.
+
+    Args:
+        waveform (Tensor): audio waveform of dimension of `(..., time)`
+        sample_rate (int): sampling rate of the waveform, e.g. 44100 (Hz)
+        gain (float): desired gain at the boost (or attenuation) in dB.
+        central_freq (float, optional): central frequency (in Hz). (Default: ``100``)
+        Q (float, optional): https://en.wikipedia.org/wiki/Q_factor (Default: ``0.707``).
+
+    Returns:
+        Tensor: Waveform of dimension of `(..., time)`
+
+    References:
+        http://sox.sourceforge.net/sox.html
+        https://www.w3.org/2011/audio/audio-eq-cookbook.html#APF
+    """
+    w0 = 2 * math.pi * central_freq / sample_rate
+    alpha = math.sin(w0) / 2 / Q
+    A = math.exp(gain / 40 * math.log(10))
+
+    temp1 = 2 * math.sqrt(A) * alpha
+    temp2 = (A - 1) * math.cos(w0)
+    temp3 = (A + 1) * math.cos(w0)
+
+    b0 = A * ((A + 1) - temp2 + temp1)
+    b1 = 2 * A * ((A - 1) - temp3)
+    b2 = A * ((A + 1) - temp2 - temp1)
+    a0 = (A + 1) + temp2 + temp1
+    a1 = -2 * ((A - 1) + temp3)
+    a2 = (A + 1) + temp2 - temp1
+
+    return biquad(waveform, b0 / a0, b1 / a0, b2 / a0, a0 / a0, a1 / a0, a2 / a0)
+
+
 def deemph_biquad(
         waveform: Tensor,
         sample_rate: int