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"""Test suites for checking numerical compatibility against Kaldi"""
import torchaudio.compliance.kaldi
from parameterized import parameterized
from torchaudio_unittest.common_utils import (
get_asset_path,
load_params,
load_wav,
skipIfNoExec,
TempDirMixin,
TestBaseMixin,
)
from torchaudio_unittest.common_utils.kaldi_utils import convert_args, run_kaldi
class Kaldi(TempDirMixin, TestBaseMixin):
def assert_equal(self, output, *, expected, rtol=None, atol=None):
expected = expected.to(dtype=self.dtype, device=self.device)
self.assertEqual(output, expected, rtol=rtol, atol=atol)
@parameterized.expand(load_params("kaldi_test_fbank_args.jsonl"))
@skipIfNoExec("compute-fbank-feats")
def test_fbank(self, kwargs):
"""fbank should be numerically compatible with compute-fbank-feats"""
wave_file = get_asset_path("kaldi_file.wav")
waveform = load_wav(wave_file, normalize=False)[0].to(dtype=self.dtype, device=self.device)
result = torchaudio.compliance.kaldi.fbank(waveform, **kwargs)
command = ["compute-fbank-feats"] + convert_args(**kwargs) + ["scp:-", "ark:-"]
kaldi_result = run_kaldi(command, "scp", wave_file)
self.assert_equal(result, expected=kaldi_result, rtol=1e-4, atol=1e-8)
@parameterized.expand(load_params("kaldi_test_spectrogram_args.jsonl"))
@skipIfNoExec("compute-spectrogram-feats")
def test_spectrogram(self, kwargs):
"""spectrogram should be numerically compatible with compute-spectrogram-feats"""
wave_file = get_asset_path("kaldi_file.wav")
waveform = load_wav(wave_file, normalize=False)[0].to(dtype=self.dtype, device=self.device)
result = torchaudio.compliance.kaldi.spectrogram(waveform, **kwargs)
command = ["compute-spectrogram-feats"] + convert_args(**kwargs) + ["scp:-", "ark:-"]
kaldi_result = run_kaldi(command, "scp", wave_file)
self.assert_equal(result, expected=kaldi_result, rtol=1e-4, atol=1e-6)
@parameterized.expand(load_params("kaldi_test_mfcc_args.jsonl"))
@skipIfNoExec("compute-mfcc-feats")
def test_mfcc(self, kwargs):
"""mfcc should be numerically compatible with compute-mfcc-feats"""
wave_file = get_asset_path("kaldi_file.wav")
waveform = load_wav(wave_file, normalize=False)[0].to(dtype=self.dtype, device=self.device)
result = torchaudio.compliance.kaldi.mfcc(waveform, **kwargs)
command = ["compute-mfcc-feats"] + convert_args(**kwargs) + ["scp:-", "ark:-"]
kaldi_result = run_kaldi(command, "scp", wave_file)
self.assert_equal(result, expected=kaldi_result, rtol=1e-4, atol=1e-5)
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