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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 | |