Table 2.

PESQ performance metric on NOIZEUS dataset (mean ± SEM) for different algorithms across various SNR levels.

Algorithm	SNR 0	SNR 5	SNR 10	SNR 15
Baseline	1.421 ± 0.009	1.600 ± 0.010	1.878 ± 0.011	2.238 ± 0.013
Iterative Wiener	1.374 ± 0.010	1.516 ± 0.011	1.687 ± 0.013	1.874 ± 0.017
Noisereduce (ours)	1.559 ± 0.008	1.854 ± 0.009	2.286 ± 0.011	2.778 ± 0.012
Savitzky-Golay	1.475 ± 0.010	1.672 ± 0.011	1.973 ± 0.012	2.353 ± 0.014
Spectral Subtraction	1.493 ± 0.010	1.733 ± 0.009	2.064 ± 0.011	2.449 ± 0.012
Subspace	1.415 ± 0.009	1.407 ± 0.008	1.380 ± 0.006	1.379 ± 0.007
Wiener	1.458 ± 0.009	1.634 ± 0.009	1.858 ± 0.011	2.095 ± 0.012