def test_kaldifeat_supports_list_of_uneven_len_inputs():
input = [
torch.arange(8000, dtype=torch.float32),
torch.arange(16000, dtype=torch.float32),
]
fe = KaldifeatFbank()
feats = fe.extract(input, sampling_rate=16000)
assert len(feats) == 2
f1, f2 = feats
assert f1.shape == (50, 80)
assert f2.shape == (100, 80)
def test_kaldifeat_supports_list_of_even_len_inputs(input):
fe = KaldifeatFbank()
feats = fe.extract(input, sampling_rate=16000)
assert feats.ndim == 3
assert feats.shape == (2, 50, 80)
def test_kaldifeat_supports_single_input_waveform(input):
fe = KaldifeatFbank()
feats = fe.extract(input, sampling_rate=16000)
assert feats.shape == (50, 80)
def test_kaldifeat_supports_list_with_single_input_waveform(input):
fe = KaldifeatFbank()
feats = fe.extract(input, sampling_rate=16000)
assert isinstance(feats, list)
assert len(feats) == 1
assert feats[0].shape == (50, 80)
def test_kaldifeat_config():
x = np.arange(8000, dtype=np.float32)
fe = KaldifeatFbank(KaldifeatFbankConfig(mel_opts=KaldifeatMelOptions(num_bins=27)))
feats = fe.extract(x, sampling_rate=16000)
assert feats.shape == (50, 27)