## 5 Evaluation Results and Discussion
### Objective Evaluation
#### 5.1.2 Performance Comparison of F0 Estimation  
Here, we show the results for the error metrics presented in Section 4.2. The improvement in this work is possible since our refinement approaches use the concept of adaptive structure. We noted several trends from the estimation error in Tables 1-3. The best value in each column is bold-faced.  
Table 1 displays the results of the evaluation of the three methods for contF0, for female and male speakers, in comparison to the YANGasf algorithm. When refining the contF0 using the time-warping (contF0_TWRP) technique, the GPE score shows an improvement of 4.46% for the BDL speaker, whereas there is only a 1.07% improvement for the JMK speaker. Nevertheless, we did not see any enhancement for the SLT speaker in the case of ContF0_TWRP. However, a 2.32% improvement was found in the refinement of contF0 based on StonMask method (ContF0_STMSK). For YANGasf, on the other hand, the improvement was 8.52%, 7.8%, and 3.08% for the BDL, JMK, and SLT speakers, respectively, in comparison with the baseline. Additionally, Table 1 shows that there is no significant difference between ContF0_STMSK and the state-of-the-art YANGasf approaches based on MFPE and STD measures in all speakers.  
In the same way, Tables 2 and 3 tabulate the GPE, MFPE, and STD measures averaged over all utterances for BDL, JMK, and SLT speakers in the presence of additive white noise and pink noise, respectively, at 0 dB of SNR to test the robustness of the contF0 tracker. adContF0-based Kalman filter (contF0_AKF) is more accurate for the female speaker (as measured by GPE) than for the other two candidates. However, this is not the case with pink noise. Moreover, adContF0-based time-warping showed better performance in terms of GPE measurement in the presence of pink noise with all speakers. In contrast, contF0_STMSK still had the lowest MFPE and STD under SNR conditions for all speakers.  
It is interesting to emphasize that the baseline does not at all meet the performance of the other refinement trackers in BDL, JMK, and SLT speakers; that the results reported in Table 1 yield results comparable with state-of-the-art algorithm, while Tables 2 and 3 strongly support the use of the proposed method-based StoneMask as the most accurate contF0 estimation algorithm. In other words, the findings in Tables 2 and 3 might demonstrate the robustness of the proposed approaches to additive Gaussian white and pink noise.  
It is worth noting that the main advantage of using adaptive Kalman filter is that we can determine our confidence in the estimates of contF0 algorithm-based TTS by adjusting SQIs to update both the measurement noise covariance and the state noise covariance. For example, it can be used to replace the one studied by [PERSON] et al. (2018) in heart rate assessment applications. Meanwhile, the time warping scheme has the ability to track the time-varying contF0 period, and reduce the amount of contF0 trajectory deviation from their harmonic locations. By considering the system processing speed, adContF0-based StoneMask is computationally inexpensive and can be useful in a practical speech processing application.  
\begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline \multirow{2}{*}{**Method**} & \multicolumn{3}{c}{**GPE \%**} & \multicolumn{3}{c}{**MFPE**} & \multicolumn{3}{c}{**STD**} \\  & **BDL** & **JMK** & **SLT** & **BDL** & **JMK** & **SLT** & **BDL** & **JMK** & **SLT** \\ \hline baseline & 12.754 & 9.850 & 7.677 & 3.558 & 3.428 & 4.421 & 4.756 & 4.513 & 6.764 \\ contF0\_AKF & 11.268 & 12.611 & 6.732 & 2.764 & 2.754 & 3.692 & 3.964 & 3.719 & 6.113 \\ contF0\_TWRP & 8.294 & 8.777 & 7.827 & 2.764 & 3.024 & 3.656 & 3.873 & 4.188 & 5.788 \\ contF0\_STMSK & 10.557 & 7.530 & 6.998 & 1.661 & 1.389 & 2.105 & 2.526 & 1.872 & 4.181 \\ \hline YANGasf & 4.231 & 2.049 & 4.592 & 1.658 & 1.452 & 2.142 & 2.239 & 1.575 & 4.160 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Average scores performance per each speaker in clean speech.