## 4 Results & Discussion
### Influence of Age Difference between Classes on Classification Accuracy  
In this scenario, we used different age distributions between PwPD and HC speakers in order to evaluate how age differences might influence detection accuracy. For these experiments, we only considered mPower, as it is the corpus with the most participants as well as a wider age range. To this end, we trained and tested new PD detection models as in the subject-wise baseline experiments. Figure 8 displays the cross-validation maximum accuracy per subset for trials employing the DARTH-VAT and AVCA toolboxes to extract features. These results were obtained employing the same RFC grid search used in the baseline. On the range of mean age difference between the PwPD and HC classes that we examined, there is a consistent positive correlation between these gaps and the accuracy achieved. We further explored the potential conflation of age and PD detection using subset \(S\) (described in Table 4). Subset \(S\) has a mean age difference of 26.6 years, though the distribution is not Gaussian. After running the same RFC grid search on subset \(S\), we found that accuracy increases even more as the mean age difference increases. Consequently,  
\begin{table}
\begin{tabular}{c c c c c c c c c c c c c} \hline \hline  & & \multicolumn{6}{c}{**AVCA**} & \multicolumn{6}{c}{**DARTH-VAT**} \\ \hline \multirow{2}{*}{**Corpus**} & \multirow{2}{*}{**Vowel**} & \multirow{2}{*}{**LSVM**} & **PCA-** & **FS-** & \multirow{2}{*}{**RFC**} & **PCA-** & **FS-** & \multirow{2}{*}{**LSVM**} & **PCA-** & **FS-** & \multirow{2}{*}{**RFC**} & **PCA-** & **FS-** \\  & & & **LSVM** & **LSVM** & & & **RFC** & **RFC** & **LSVM** & & **LSVM** & & **RFC** & **RFC** \\ \hline Neurovoz & /a/ & 56.2 & 64.0 & **65.2** & **85.4** & 77.0 & 83.1 & **56.7** & 56.2 & 56.2 & 79.8 & 62.4 & **82.0** \\  & /e/ & 63.0 & **68.5** & 64.4 & 78.1 & 76.0 & **80.1** & 56.1 & 63.7 & 59.6 & **76.7** & 74.0 & 73.3 \\  & /i/ & 70.9 & **76.2** & 59.3 & **86.0** & 80.2 & 85.5 & 55.2 & **59.9** & 54.1 & **83.7** & 75.0 & 82.6 \\  & /o/c/ & 58.8 & **69.4** & 57.6 & **81.2** & 76.5 & 80.6 & 53.5 & 54.1 & **56.5** & 77.6 & 58.8 & **78.2** \\  & /u/z/ & 61.3 & **64.0** & 59.4 & 77.5 & 76.6 & **79.3** & **61.3** & 55.9 & 53.2 & **86.5** & 69.4 & 83.8 \\ \hline ItalianPVS & /a/ & 94.9 & 91.9 & **99.0** & 99.0 & 97.0 & **100.0** & 58.6 & 65.7 & **79.8** & **99.0** & 72.7 & **99.0** \\  & /e/ & 87.9 & 86.9 & **98.0** & 99.0 & 93.9 & **100.0** & 49.5 & 59.6 & **79.8** & **99.0** & 82.8 & **99.0** \\  & /i/ & 92.9 & 92.9 & **97.0** & 99.0 & 98.0 & **100.0** & 50.5 & 58.6 & **94.9** & **99.0** & 64.6 & **99.0** \\  & /o/c/ & 89.9 & 89.9 & **97.0** & **99.0** & 93.9 & 98.0 & 51.6 & 52.7 & **90.3** & **98.9** & 77.4 & **98.9** \\  & /u/z/ & 78.8 & 91.9 & **92.9** & **98.0** & 97.0 & **98.0** & 53.3 & 52.5 & **58.6** & **99.0** & 76.8 & **99.0** \\ \hline mPower & /a/ & 51.1 & **59.2** & 55.1 & **75.4** & 67.1 & 69.4 & 52.3 & 50.9 & **53.6** & **70.4** & 70.2 & **70.4** \\ \hline \hline \end{tabular}
\end{table}
Table 13: Accuracy (%) in the record-wise experiments. This scenario is described in Section 3.4.2. Highest accuracy per vowel, coefficient, classifier, feature reduction strategy, and corpus are in bold.  
the results suggest that a difference in the mean age between speakers with and without PD could be leading to overoptimistic results, as age-related effects on the voice of the speakers can bias the classifier.