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from basis import ScoreBasis | |
import numpy as np | |
from pesq import pesq | |
from scores.helper import wss, llr, SSNR, trim_mos | |
class CBAK(ScoreBasis): | |
def __init__(self): | |
super(CBAK, self).__init__(name='CBAK') | |
self.score_rate = 16000 | |
self.intrusive = False | |
def windowed_scoring(self, audios, score_rate): | |
if len(audios) != 2: | |
return None | |
return cal_CBAK(audios[0], audios[1], score_rate) | |
def cal_CBAK(target_wav, pred_wav, fs): | |
alpha = 0.95 | |
# Compute WSS measure | |
wss_dist_vec = wss(target_wav, pred_wav, fs) | |
wss_dist_vec = sorted(wss_dist_vec, reverse=False) | |
wss_dist = np.mean(wss_dist_vec[:int(round(len(wss_dist_vec) * alpha))]) | |
# Compute the SSNR | |
snr_mean, segsnr_mean = SSNR(target_wav, pred_wav, fs) | |
segSNR = np.mean(segsnr_mean) | |
# Compute the PESQ | |
pesq_raw = pesq(fs, target_wav, pred_wav, 'wb') | |
# Cbak | |
Cbak = 1.634 + 0.478 * pesq_raw - 0.007 * wss_dist + 0.063 * segSNR | |
Cbak = trim_mos(Cbak) | |
return Cbak | |