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from basis import ScoreBasis
import numpy as np
class SSNR(ScoreBasis):
def __init__(self):
super(SSNR, self).__init__(name='SSNR')
self.intrusive = False
def windowed_scoring(self, audios, score_rate):
if len(audios) != 2:
raise ValueError('SSNR needs a reference and a test signals.')
return cal_SSNR(audios[0], audios[1], score_rate)
def cal_SSNR(ref_wav, deg_wav, srate=16000, eps=1e-10):
# obtained from https://github.com/wooseok-shin/MetricGAN-plus-pytorch/blob/main/metric_functions/metric_helper.py
""" Segmental Signal-to-Noise Ratio Objective Speech Quality Measure
This function implements the segmental signal-to-noise ratio
as defined in [1, p. 45] (see Equation 2.12).
"""
clean_speech = ref_wav
processed_speech = deg_wav
clean_length = ref_wav.shape[0]
processed_length = deg_wav.shape[0]
# scale both to have same dynamic range. Remove DC too.
clean_speech -= clean_speech.mean()
processed_speech -= processed_speech.mean()
processed_speech *= (np.max(np.abs(clean_speech)) / np.max(np.abs(processed_speech)))
# global variables
winlength = int(np.round(30 * srate / 1000)) # 30 msecs
skiprate = winlength // 4
MIN_SNR = -10
MAX_SNR = 35
# For each frame, calculate SSNR
num_frames = int(clean_length / skiprate - (winlength/skiprate))
start = 0
time = np.linspace(1, winlength, winlength) / (winlength + 1)
window = 0.5 * (1 - np.cos(2 * np.pi * time))
segmental_snr = []
for frame_count in range(int(num_frames)):
# (1) get the frames for the test and ref speech.
# Apply Hanning Window
clean_frame = clean_speech[start:start+winlength]
processed_frame = processed_speech[start:start+winlength]
clean_frame = clean_frame * window
processed_frame = processed_frame * window
# (2) Compute Segmental SNR
signal_energy = np.sum(clean_frame ** 2)
noise_energy = np.sum((clean_frame - processed_frame) ** 2)
segmental_snr.append(10 * np.log10(signal_energy / (noise_energy + eps)+ eps))
segmental_snr[-1] = max(segmental_snr[-1], MIN_SNR)
segmental_snr[-1] = min(segmental_snr[-1], MAX_SNR)
start += int(skiprate)
return sum(segmental_snr) / len(segmental_snr)
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