Add allpass filter to functional (#444)

docs/source/functional.rst

@@ -83,6 +83,11 @@ Functions to perform common audio operations.
 
 .. autofunction:: highpass_biquad
 
+:hidden:`allpass_biquad`
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+.. autofunction:: allpass_biquad
+
 :hidden:`equalizer_biquad`
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 

test/test_functional_filtering.py

@@ -148,6 +148,26 @@ class TestFunctionalFiltering(unittest.TestCase):
         assert torch.allclose(sox_output_waveform, output_waveform, atol=1e-3)
         _test_torchscript_functional(F.highpass_biquad, waveform, sample_rate, CUTOFF_FREQ)
 
+    def test_allpass(self):
+        """
+        Test biquad allpass filter, compare to SoX implementation
+        """
+
+        CENTRAL_FREQ = 1000
+        Q = 0.707
+
+        noise_filepath = os.path.join(self.test_dirpath, "assets", "whitenoise.mp3")
+        E = torchaudio.sox_effects.SoxEffectsChain()
+        E.set_input_file(noise_filepath)
+        E.append_effect_to_chain("allpass", [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.allpass_biquad(waveform, sample_rate, CENTRAL_FREQ, Q)
+
+        assert torch.allclose(sox_output_waveform, output_waveform, atol=1e-4)
+        _test_torchscript_functional(F.allpass_biquad, waveform, sample_rate, CENTRAL_FREQ, Q)
+
     def test_equalizer(self):
         """
         Test biquad peaking equalizer filter, compare to SoX implementation

torchaudio/functional.py

@@ -22,6 +22,7 @@ __all__ = [
     "lfilter",
     "lowpass_biquad",
     "highpass_biquad",
+    "allpass_biquad",
     "equalizer_biquad",
     "biquad",
     'mask_along_axis',
@@ -794,6 +795,35 @@ def lowpass_biquad(waveform, sample_rate, cutoff_freq, Q=0.707):
     return biquad(waveform, b0, b1, b2, a0, a1, a2)
 
 
+def allpass_biquad(waveform, sample_rate, central_freq, Q=0.707):
+    # type: (Tensor, int, float, float) -> Tensor
+    r"""Design two-pole all-pass filter.  Similar to SoX implementation.
+
+    Args:
+        waveform(torch.Tensor): audio waveform of dimension of `(..., time)`
+        sample_rate (int): sampling rate of the waveform, e.g. 44100 (Hz)
+        central_freq (float): central frequency (in Hz)
+        q_factor (float): https://en.wikipedia.org/wiki/Q_factor
+
+    Returns:
+        output_waveform (torch.Tensor): 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
+
+    b0 = 1 - alpha
+    b1 = -2 * math.cos(w0)
+    b2 = 1 + alpha
+    a0 = 1 + alpha
+    a1 = -2 * math.cos(w0)
+    a2 = 1 - alpha
+    return biquad(waveform, b0, b1, b2, a0, a1, a2)
+
+
 def equalizer_biquad(waveform, sample_rate, center_freq, gain, Q=0.707):
     # type: (Tensor, int, float, float, float) -> Tensor
     r"""Design biquad peaking equalizer filter and perform filtering.  Similar to SoX implementation.