test_vad.py 文件源码

def test_calculate_SNR_positive_1(self):
        source_array = [89, -89] * 6000 + [502, -502] * 8000 + [89, -89] * 7000
        source_data = reduce(
            lambda a, b: a + struct.pack('>h', b), source_array[1:], struct.pack('>h', source_array[0])
        )
        sampling_frequency = 8000
        bounds_of_speech = [(2.0 * 6000.0 / sampling_frequency, 2.0 * (6000.0 + 8000.0) / sampling_frequency)]
        silence_energy = reduce(
            lambda a, b: a + b * b,
            source_array[0:(2 * 6000)] + source_array[(2 * (6000 + 8000)):],
            vad.EPS
        ) / (2.0 * (6000.0 + 7000.0))
        speech_energy = reduce(
            lambda a, b: a + b * b,
            source_array[(2 * 6000):(2 * (6000 + 8000))],
            vad.EPS
        ) / (2.0 * 8000.0)
        target_snr = 20.0 * math.log10(speech_energy / silence_energy)
        self.assertAlmostEqual(target_snr, vad.calculate_SNR(source_data, sampling_frequency, bounds_of_speech))