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]