## 4 Discussion  
The temporal domain's acoustic features appear to be more informative in assessing oral turns regardless of the speaker. Out of the seven selected features listed in Table 2, four variables specifically pertain to temporal aspects. This outcome is promising because computing such features, unlike those in the F0 or spectral domain, demonstrates greater resilience against adverse conditions that may arise with users affected by DS. Generally, pitch detection algorithms encounter more challenges when dealing with pathological voices compared to typical voices [39]. Moreover, features related to the temporal domain can be readily associated with disfluent speech, such as stuttering or cluttering, which, while not universal, are common issues among this population [40; 41; 42]. The presentation of individual reports about oral production proficiency of the speakers has proven to be necessary to be accurate in the judgments concerning the particular deficits of the speakers. We have shown in Figure 2 that presenting the personal results permits us to make a diagnosis that takes into account the important inter-speaker differences. Presenting results that take into account the different prosodic features is especially important in this context, as the subjective evaluation could be dependent on many aspects. The presented reports permit us to shed light on the particular features that could most influence therapists' decisions when they score the quality of DS utterances. We already highlighted in previous works the high variability among DS individuals [24]. The five speakers exhibit different patterns with clear differences among them; the shapes of the red areas in the graphics are different among them and contrast significantly with the one of the typical speakers. As expected, the graphics corresponding to utterances labeled as wrong are more distant to the mean TD pattern and closer to the borders of the reference interval. All the speakers have lower values of the feature d1 (loudnessPeaksPerSec) than TD speakers, related with the speed of speech. They are clearly slower when compared to the typical values, close to the limit of the reference interval in all the cases except 024. Speakers 022 and 024 show lower values for the feature loudness_sma3_percentile20.0 (e1). We already pointed out that low speed and abnormal control of loudness are characteristic clues of these types of speakers, probably due to muscular hypotonia [9]. Abnormal higher values for jitter (f1) are observed in the cases of speakers 022 and 023 and in a lower degree in the case of 026. The fact that the differences are higher in the cases of utterances labeled as wrong by the therapist seems to indicate that these speakers exhibit a particular problem with the control of this feature. As the jitter has to do with changes in the dynamics of the F0 contour, these speakers could be evidencing an unsatisfactory control of pitch. The graphs allow us to find a problematic use of speech rhythm in the case of speaker 023. The StddevVoicedSegmentLengthSec feature (d2) varies much more than typically. This speaker shows a problem of cluttered speech with unstable duration of the segments, providing a higher standard deviation of voiced segments lengths than in a typical voice. This behavior is also observed in speakers 025 and 026 but to a lesser degree. The two speakers that were expected to have the worst results are 025 and 026 due to their lower CA and VA (see Table 1). Apart from the extreme values of d1 that has been already mentioned (they speak extremely slow), speaker 026 has the highest values for d3, d4, and d5 features, evidencing that this speaker interrupts himself very frequently, more when the utterances are labeled as wrong. In the case of speaker 025, wrong utterances are marked when there are more pauses as well (higher d5, d4, d3, and d2 values).