def test_sph_files(self, file, fails):
# Some SPHERE files can be read with soundfile, but not all.
path = get_file_path(file)
if fails:
with pytest.raises(RuntimeError):
load_audio(path)
else:
load_audio(path)
def test_mfcc(self):
path = get_file_path("sample.wav")
y = audioread(path)[0]
y_filtered = transform.mfcc(y)
tc.assert_equal(y_filtered.shape, (291, 13))
tc.assert_isreal(y_filtered)
def test_mfcc(self):
path = get_file_path("sample.wav")
y = audioread(path)[0]
yFilterd = transform.ssc(y)
tc.assert_equal(yFilterd.shape, (294, 26))
tc.assert_isreal(yFilterd)
def test_fbank(self):
path = get_file_path("sample.wav")
y = audioread(path)[0]
feature = transform.fbank(y)
tc.assert_equal(feature.shape, (240, 23))
tc.assert_isreal(feature)
tc.assert_array_greater_equal(feature, 0)
def setUp(self):
path = get_file_path("sample.wav")
self.time_signal = load_audio(path)
# self.time_signal = np.random.randn(5, 3, 5324)
self.torch_signal = torch.from_numpy(self.time_signal)
self.stft = STFT(size=self.size,
shift=self.shift,
window_length=self.window_length,
fading=self.fading,
complex_representation='concat',
window=self.window)
self.fbins = self.stft.size // 2 + 1
def setUp(self):
self.ref_path = get_file_path('speech.wav')
self.deg_path = get_file_path('speech_bab_0dB.wav')
self.ref_array = pb.io.load_audio(self.ref_path)
self.deg_array = pb.io.load_audio(self.deg_path)
def setUp(self):
path = get_file_path("sample.wav")
self.x = audioread(path)[0]