# Objective Assessment of Porcine Voice Acoustics for Laryngeal Surgical Modeling
## 4 Discussion
### Other Parameters  
Most of the remaining parameters did not show a significant change between pre- and post-surgery as can be seen in Figure 5. Q50\({}_{\text{n}}\) can be interpreted as stating the number of the partial window in the signal where higher harmonics are least dominant (excluding edge windows). All values are therefore integers from 2 to 10. Only pig 2 exhibited a subjective change. Similar to the partial window properties discussed above, the reduced data richness of this parameter limits its usefulness. The squeal duration (Dur) also did not show a significant change for all pigs between pre- and post-surgery, contrary to our expectations (see hypotheses in Table S2), even slightly increasing after surgery for all pigs. This finding suggests that squeal duration may be controlled more by behaviors inherent to pig communication rather than by the physiology of the vocal fold state. The slight increase in squeal duration may be meaningful, but more data are needed for verification. Spectral flatness parameters SF\({}_{\text{Q50}}\) and SF were calculated similarly; the main difference was that SF\({}_{\text{Q50}}\) was scaled using Q50. We expected spectral flatness to increase as post-surgery squeals appear to become \"noisier\", but no such trend could be observed in  
Figure 6: Averaged spectral energy of 10 squeals of pig 3 (**a**) before and (**b**) after surgery. Energy spectra were calculated using 1024 data point windows with 50% overlap. A distinct energy reduction at higher frequencies can be seen, resulting in lower PF and Q-parameters. all pigs. The decrease in SFG50 can be largely attributed to the Q50 scaling and therefore has no additional information value. Flux did show a consistent trend of increasing after surgery in all pigs. Acoustically, Flux can be thought of as a time-instability of the voice. Higher values typically indicate greater variation in energy spectra over time. In Figure 7, the averaged normalized magnitude spectrum of 10 squeals pre- and post-surgery is depicted for two neighboring consecutive time windows within the squeal (consecutive windows 10 and 11 with 50% overlap). For the calculation of Flux, first the quadratic difference between these neighboring windows, the red line, is calculated. As can be seen in the figure, this difference is especially large for the steep inclines in the low-frequency range of post-surgery spectra. Furthermore, since the difference is calculated quadratically, a single large deviation between neighboring windows is often bigger than multiple smaller ones. The reduced high-frequency energy that led to decreased Q-parameters also therefore impacts Flux. Flux is the sum of all these differences over frequencies and time and therefore increases after surgery. We expected RMSI to increase after surgery, as squeals lose structure, leading to less dominant global peaks in the acoustic signal and hence a higher RMSI (see Table S2). RMSI increased for all pigs after surgery on average, but none of these changes was significant. Interestingly, contrary to our expectations (see Table S2), HNR increased after surgery, indicating, by definition of the parameter, stronger harmonics. However, this is obviously not the case as can be seen in Figure 5, since even in pig 3 with diminishing higher frequencies after surgery, HNR increased. The algorithm of HNR is rather complex and even if it can theoretically be calculated on aperiodic signals, it was not designed for this purpose [15]. The reason for the increase in HNR after surgery may therefore be the following: Even in the most aperiodic of signals, the HNR algorithm still searches for the best possible F0 candidate [28]. As the squeals post-surgery lose most of their higher frequencies, this peak may be more consistently found within the same low frequency range for all windows. This leads, in comparison to pre-surgery, to a more dominant \"F0\" peak and, as the F0 peak is part of the harmonics, to a higher harmonics-to-noise ratio (higher HNR).