## 4 Discussion and Conclusions  
The current study focused on how TA and CT muscle activation levels control various acoustic and posturing features of voice production. Lung pressure, LCA, and IA activation levels were varied as a function of TA and CT activation levels such that the phonation threshold pressure was always exceeded. PCA muscle activation was set to 0%. The results suggested that \(f_{o}\) and SPL increase with CT activation, while NSC decreases when CT activation is raised above 20%. With TA activation, acoustic features have no uniform trends, except that SPL increases uniformly with TA if there is a co-variation with CT activation. The postural features L, \(\sigma_{SLLP}\), \(\sigma_{olig}\), and \(\sigma_{mus}\) increase with an increase in CT activation. Also, \(\sigma_{mus}\) increase whereas L, \(\sigma_{SLLP}\), and \(\sigma_{lig}\) decrease with an increase in TA activation. Aperiodicity roughness was found to be the most complex feature to quantify among all the acoustic and postural features that were studied in the current study. In the current study, signal-to-noise ratio, harmonic-to-noise ratio, smoothed cepstral peak prominence [15, 16], correlation dimension [18], sample entropy [19], and approximate entropy were tried to appropriately quantify aperiodicity roughness in a signal. None of these acoustic features was completely accurate in measuring roughness in the signals generated by varying TA and CT muscle activations. Approximate entropy was found to be the best among them, as judged by visual inspection of signal aperiodicity and tests on sinusoidal signals with variable amounts of roughness. However, even ApEn does not give smooth contours in the muscle activation plots, suggesting that further research needs to be conducted to obtain an acoustic feature that can accurately quantify aperiodicity in a voice signal. Comparing our results with findings from previous studies sheds more light on the relationship between input and output variables. [PERSON] et al., (1989) [32] used electromyography on four subjects to study the role of CT and TA muscle activations in the regulation of fundamental frequency of phonation. Similar to the current findings,\(f_{o}\) increased with increase in CT activation at low TA values. There was also a decrease in \(f_{o}\) with increase in TA activation at high CT levels. No phonation was produced at extremely high TA and low CT by these subjects. They were not asked to produce anything higher than 440 Hz. We observed phonation above 440 Hz in our model, but the data were sparse with relatively large lung pressures and more irregularity. It is well known that subglottal pressure plays a major role in the control of intensity. Our study confirmed this. Aside from P\({}_{L}\), CT activation had a major impact on SPL. This is probably due to the  
Figure 11: Muscle activation plots for fiber stress in **(left)** SLLP layer, **(center)** ligament layer, and **(right)** TA muscle with respect to TA–CT muscle activations. increased radiation efficiency with higher \(f_{o}\)[52]. Every doubling of \(f_{o}\) adds at least 6 dB to the radiated sound pressure level. No prior formal study has related a brightness feature like the normalized spectral centroid (NSC), or a roughness feature like approximate entropy (ApEn), to intrinsic laryngeal muscle activations. Hence, we could not compare our results against findings from other studies. Relations obtained for NSC and ApEn were much more complex than those obtained for \(f_{o}\) and SPL. Qualitatively, periodicity is related to the dominance of a single mode of vibration and entrainment of other modes to this dominant mode. When the ligament and the TA muscle fibers do not have similar natural mode frequencies, there is often not the required entrainment. This leads to aperiodic vibration. Such rough phonation was observed in many regions of the muscle activation plot.