# Assessment of Self-Supervised Denoising Methods for
## 3 Results  
Figure 7 shows the spectrograms of the original ES and VF wave files and their corresponding white noise wave files.  
The spectrograms of both the original ES and the VF test files show clear frequency bands with high power density in yellow, suggesting a strong signal presence. For the noised ES file and the noised VF wave file, the spectrograms show a more uniform power distribution across frequencies with less defined bands than the original. This indicates the presence of noise, which has spread the signal power more uniformly, making the frequency bands less distinct.  
Table 3 resumes the test outcomes of the different experiments described in Table 2, using the trained models of DCUNET and DCUNET-cTSTM. These test results were evaluated by objective metrics: SNR, SSNR, PESQ-WB, PESQ-NB, and STOI. The bold numbers denote the best results of the metrics.  
After the training phase, we conducted a mismatch condition (for example, trained on VB8 and tested with ES), using the pre-trained models from the four experiments to denoise various speech test signals. Figure 8 illustrates the resulting spectrograms of an ES test wave file, while Figure 9 displays the testing outcomes with cleaned VF wave files. Audio samples of the results are presented at the following demo link: [[https://madipraise.github.io/ES/](https://madipraise.github.io/ES/)]([https://madipraise.github.io/ES/](https://madipraise.github.io/ES/))  
\begin{table}
\begin{tabular}{c c c} \hline \hline  & **DCUNET** & **DCUNET-cTSTM** \\ \hline Sampling rate & 16 kHz & 16 kHz \\ Window size & 64 ms Hamming window & 64 ms Hamming window \\ Number of layers & 10 & 10 \\ Number of channels & (45, 90, 90, 90, 90, 90, 90, 90, 90, 90, 90, 90, 90, 90, 90, 9  
Figure 7: Spectrograms of ES and VF wave files, and of their corresponding noised wave files.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Training** & **Model** & **SNR** & **SSNR** & **PESQ-NB** & **PESQ-WB** & **STOI** \\ \hline Experiment 1 & \begin{tabular}{c} DCUNET \\ DCUNET- \\ cTSTM \\ \end{tabular} & \(-19.25\pm 21.93\) & \(-10\pm 15.84\) & \(1.01\pm 4.15\) & \(1.01\pm 3.15\) & \(0.17\pm 0.97\) \\ \hline Experiment 2 & \begin{tabular}{c} DCUNET \\ DCUNET- \\ cTSTM \\ \end{tabular} & \(\mathbf{0.48\pm 14.82}\) & \(-7.17\pm 10.17\) & \(1.16\pm 3.33\) & \(1.05\pm 2.36\) & \(0.43\pm 0.97\) \\ \hline Experiment 3 & \begin{tabular}{c} DCUNET \\ DCUNET- \\ cTSTM \\ \end{tabular} & \(\mathbf{0.81\pm 15.61}\) & \(\mathbf{-6.91\pm 10.17}\) & \(\mathbf{1.24\pm 3.42}\) & \(\mathbf{1.071\pm 2.61}\) & \(\mathbf{0.44\pm 0.97}\) \\ \hline Experiment 3 & \
\begin{tabular}{c} DCUNET \\ cTSTM \\ \end{tabular} & \(-2.97\pm 19.17\) & \(-7.02\pm 10.98\) & \(1.22\pm 3.09\) & \(1.02\pm 2.08\) & \(0.42\pm 0.99\) \\ \hline Experiment 4 &
\begin{tabular}{c} DCUNET \\ DCUNET- \\ cTSTM \\ \end{tabular} & \(-15.73\pm-0.01\) & \(-6.44\pm-0.58\) & \(1.02\pm 1.55\) & \(1.01\pm 2.09\) & \(-0.17\pm 0.50\) \\ \hline \hline \end{tabular}
\end{table}
Table 3: Results of the four experiments using the DCUNET and DCUNET-cTSTM.  
Figure 8: Spectrograms of the ES test file using the pre-trained models of the four experiments.