# Investigation of Vocal Fatigue Using a Dose-Based Vocal Loading Task
## 5 Data Analysis Results and Discussions
### Acoustic Feature Analysis  
The cross-session variations of the mean and confidence level (95%) of the features for all participants are shown in Figure 7. The NSA data of participant No.1 was unavailable due to sensor failure. The \(f\)0, SPL, and duty ratio in Figure 7 follow a similar trend. They increase rapidly at the beginning, reach a certain saturation level over the remaining sessions. \(f\)0, SPL, and duty ratio indicated a vocal adjustment over session S1. The mean value variations of these three features from S1 to S2 were at least 100% larger than those of any other following VLT session. The \(f\)0 had the minimal mean value variation (<2 Hz) in the last three sessions. The SPL mean value decreased by 2 dB after S4 and increased by 1 dB after S5. The duty ratio mean value increased by 2% from one plateau (S2-S4) to another (S5-S6). The trends in \(f\)0, SPL and duty ratio were largely consistent with the trends in CAPE-V and SAVRa ratings.  
A considerable decrease in CPP was found to be related to the presence of dysphonia by Heman-Ackah [16]. The CPP_MIC in Figure 7 showed a slight increase (0.15 dB) from S1 to S2, and a decrease (0.3 dB) from S3 to S4. The fluctuation of the CPP_MIC from S1 to S6 was less than 2%, which means that the variation of CPP_MIC was not significant. The CPP_NSA showed a sharp increase (2 dB) in the late session after sustaining a relatively low level for the first three sessions. The  
Figure 6: Mean counts of vocal fatigue symptom appearances for all participants during the VLTs in terms of session. The vertical blue dash lines separate different VLT sessions.  
jitter_MIC increased rapidly from S1 to S4 by 10% but decreased by 5% afterwards, which was not well correlated with the subjective rating results for the VLT sessions. The jitter_NSA showed a trend similar to jitter_MIC, but with a larger decrease after S3. The mean values of the shimmer_MIC and shimmer_NSA were well correlated (\(r=0.91,p=0.987\)). Their progressions were similar to that of the \(f0\). This indicates that the loudness perturbation increased rapidly in the early sessions, and saturated at a high level over the last sessions.  
A decrease in spectral tilt slope was found to correlate with stressed phonation by [PERSON] and [PERSON] [46]. A decrease in spectral tilt slope indicates that higher frequencies are increased more than lower frequencies. In Figure 7, the TILT_MIC slopes and the TILT_NSA slopes decreased from S1 to S6 in general. Thus, the high frequencies of both the microphone and NSA spectra increased throughout VLT sessions. [PERSON] and [PERSON] found that vocal fry had a higher HRF value than modal and breathy voice [47]. The HRF_MIC and the HRF_NSA obeyed similar trends than TILT_MIC and TILT_NSA. The HRF_MIC was well correlated (\(r=0.94,p=0.98\)) with HRF_NSA. These two features showed identical trends. The HRF mean values decreased from S1 and converged to S6. The H1H2_NSA decreased by 50% from S1 to S6, and remained constant from S2 to S5. A comprehensive analysis of the Pearson correlation between each pair of features is shown in Table 6. There are two groups of well correlated (>90%) features. The first group includes \(f0\), SPL_MIC, duty ratio, shimmer_MIC, and shimmer_NSA. The first group shows a rapid increase in early session followed by saturation. The second group includes TILT_MIC, TILT_NSA, HRF_MIC, and HRF_NSA and shows a general decrease from S1 to S6.  
Figure 7: Cross-session variations of means and confidential levels in terms of feature for all participants.