[audio utils] fix fft_bin_width computation (#36603)
* fix fft_bin_width computation * update docstring + enforce correct params * update test with correct value * udpate test * update feature extractors for concerned models * update * make * udpate docstring * udpate docstring
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@@ -194,26 +194,38 @@ class AudioUtilsFunctionTester(unittest.TestCase):
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triangularize_in_mel_space=True,
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)
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# fmt: off
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# here the expected values from torchaudio.compliance.kaldi.get_mel_banks
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# note that we compute values in float64 while they do it in float32
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expected = np.array(
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[[0.0000, 0.0000, 0.0000, 0.0000],
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[0.6086, 0.0000, 0.0000, 0.0000],
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[0.8689, 0.1311, 0.0000, 0.0000],
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[0.4110, 0.5890, 0.0000, 0.0000],
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[0.0036, 0.9964, 0.0000, 0.0000],
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[0.0000, 0.6366, 0.3634, 0.0000],
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[0.0000, 0.3027, 0.6973, 0.0000],
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[0.0000, 0.0000, 0.9964, 0.0036],
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[0.0000, 0.0000, 0.7135, 0.2865],
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[0.0000, 0.0000, 0.4507, 0.5493],
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[0.0000, 0.0000, 0.2053, 0.7947],
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[0.0000, 0.0000, 0.0000, 0.9752],
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[0.0000, 0.0000, 0.0000, 0.7585],
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[0.0000, 0.0000, 0.0000, 0.5539],
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[0.0000, 0.0000, 0.0000, 0.3599],
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[0.0000, 0.0000, 0.0000, 0.1756]]
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[
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[0.0000000000000000, 0.0000000000000000, 0.0000000000000000, 0.0000000000000000],
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[0.6457883715629578, 0.0000000000000000, 0.0000000000000000, 0.0000000000000000],
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[0.8044781088829041, 0.1955219060182571, 0.0000000000000000, 0.0000000000000000],
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[0.3258901536464691, 0.6741098165512085, 0.0000000000000000, 0.0000000000000000],
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[0.0000000000000000, 0.9021250009536743, 0.0978749766945839, 0.0000000000000000],
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[0.0000000000000000, 0.5219038724899292, 0.4780961275100708, 0.0000000000000000],
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[0.0000000000000000, 0.1771058291196823, 0.8228941559791565, 0.0000000000000000],
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[0.0000000000000000, 0.0000000000000000, 0.8616894483566284, 0.1383105516433716],
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[0.0000000000000000, 0.0000000000000000, 0.5710380673408508, 0.4289619624614716],
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[0.0000000000000000, 0.0000000000000000, 0.3015440106391907, 0.6984559893608093],
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[0.0000000000000000, 0.0000000000000000, 0.0503356307744980, 0.9496643543243408],
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[0.0000000000000000, 0.0000000000000000, 0.0000000000000000, 0.8150880336761475],
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[0.0000000000000000, 0.0000000000000000, 0.0000000000000000, 0.5938932299613953],
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[0.0000000000000000, 0.0000000000000000, 0.0000000000000000, 0.3851676583290100],
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[0.0000000000000000, 0.0000000000000000, 0.0000000000000000, 0.1875794380903244],
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],
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dtype=np.float64,
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)
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# fmt: on
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self.assertTrue(np.allclose(mel_filters, expected, atol=5e-5))
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# kaldi implementation does not compute values for last fft bin
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# indeed, they enforce max_frequency <= sampling_rate / 2 and
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# therefore they know that last fft bin filter bank values will be all 0
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# and pad after with zeros
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# to comply with our API for `mel_filter_bank`, we need to also pad here
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expected = np.pad(expected, ((0, 1), (0, 0)))
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self.assertTrue(np.allclose(mel_filters, expected))
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def test_mel_filter_bank_slaney_norm(self):
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mel_filters = mel_filter_bank(
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@@ -369,7 +381,7 @@ class AudioUtilsFunctionTester(unittest.TestCase):
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self.assertTrue(np.allclose(spec[:64, 400], expected))
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mel_filters = mel_filter_bank(
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num_frequency_bins=256,
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num_frequency_bins=257,
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num_mel_filters=400,
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min_frequency=20,
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max_frequency=8000,
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@@ -379,8 +391,6 @@ class AudioUtilsFunctionTester(unittest.TestCase):
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triangularize_in_mel_space=True,
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)
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mel_filters = np.pad(mel_filters, ((0, 1), (0, 0)))
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spec = spectrogram(
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waveform,
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window_function(400, "povey", periodic=False),
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@@ -510,7 +520,7 @@ class AudioUtilsFunctionTester(unittest.TestCase):
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self.assertTrue(np.allclose(spec_list[2][:64, 400], expected3))
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mel_filters = mel_filter_bank(
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num_frequency_bins=256,
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num_frequency_bins=257,
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num_mel_filters=400,
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min_frequency=20,
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max_frequency=8000,
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@@ -520,8 +530,6 @@ class AudioUtilsFunctionTester(unittest.TestCase):
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triangularize_in_mel_space=True,
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)
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mel_filters = np.pad(mel_filters, ((0, 1), (0, 0)))
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spec_list = spectrogram_batch(
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waveform_list,
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window_function(400, "povey", periodic=False),
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