## 4 Results and Analyses
### The Effect of VTLN: Analysis by Gender  
In this section, we split the results based on gender (only two genders, male and female, are provided in the meta data, so we will use this binary split). Figure 4 displays the WERs for the female speakers (red lines) and the male (blue lines) speakers (for whom age information is available) across the different ages for the three different models and the two speaking styles. Table 12 summarizes the average WERs for both genders (over all speakers, including those for which no age information was available) per speaker group and per speaking style for the three models. From Figure 4 and Table 12, we can observe:  
* Dutch native children (DC; ages 6 to 13 years): For both read and HMI speech, the earlier observed trend of decreasing WER with increasing age holds for both male and female speakers. Without any normalization (solid lines), WER is higher for females compared to males (see also Table 12). Applying VTLN has the largest effect on the female speakers: for both VTLN conditions, the WER of the female speakers is lower than that of the male speakers. The effect is largest when VTLN is applied during both training and testing (dotted lines). These results are likely due to the higher-pitched female voices compared to the male voices.
* Dutch native teenagers (DT; ages 12 to 18 years): For read speech, for all of the models female speech is recognized better than male speech. Applying VTLN seems to have a positive effect on both genders, except that the effect seems to be a bit larger for the youngest female speakers, i.e., the 12 year old, which is in line with the findings for the female child speakers in the DC group (see the left-most panel in Figure 4). For HMI speech, the same picture holds except that the effect of applying VTLN results in slightly degraded performance for the male speakers (see Table 12). In Figure 4, the fluctuations in performance observed for the 15, 16, and 17 year old female speakers are due to a small number of speakers per age (1, 6, and 1, respectively).
* Dutch non-native teenagers (NnT; ages 12 to 18 years): For the Dutch non-native teenagers, WERs were lower for the female speakers compared to the male speakers for both read and HMI speech. This gender gap was particularly large for the more spontaneous HMI speech. Overall, applying VTLN improved recognition performance for both the female and male speakers for read speech, and approximately to the same extent (Table 12). For HMI speech, no improvement was found when applying VTLN for the male speakers, while a small improvement was found for the female speakers for the model where VTLN was applied during testing. As shown in Figure 4, this small improvement was driven by the younger female speakers, where the largest improvement was found--in line with the earlier age results.  
In summary, for all speaker groups and both speech types, the average WER over all of the models was always lower for the female speakers than the male speakers (see Table 12, bottom row), which is in line with earlier findings on this data set [27]. Overall, the use of VTLN was similar for both genders, except for the Dutch children speaker group, which showed a larger improvement for the female speakers (5.3% for read and 3.2% for HMI speech) compared to the male speakers (3.7% for read and 1.0% for HMI speech), which was largely driven by the improvement for the youngest female speakers. This gender gap can be explained by the higher-pitched voices of especially the younger female speakers, which could then benefit most from the normalization step.