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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:
raise ValueError('CBAK needs a reference and a test signals.')
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
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