## 3 Results  
### Impact of Noise on Auditory Sustained Attention  
After the data were processed, OE, CE, and MRT were calculated in both pink and speech-noise environments, and all subjects' experimental data met the 2-fold standard-deviation intra-group consistency reliability test.  
Figure 5 shows the influence of noise types on auditory sustained attention. The results show that the curves of OE, CE, and MRT change in the same trend when auditory sustained attention is disturbed by pink and speech noise, that is, they all decrease as the SNR increases. Interference noise can cause irrelevant sound effects, which can distract people's attention and cause emotional tension. In this study, it is possible that under low SNR conditions, noise influenced the detection or recognition of target stimuli, resulting in longer reaction times and an increase in both OE and CE. Significance analysis of OE, CE, and MRT in different noise environments showed that the differences between OE (\(p\) = 0.480), CE (\(p\) = 0.416), and MRT (\(p\) = 0.691), corresponding to pairwise noises, were not significant. The impact of the signal-to-noise ratio on auditory sustained attention was significant for OE (\(p\) = 0.000), CE (\(p\) = 0.000), and MRT (\(p\) = 0.000). To further determine the data differences between different SNR conditions, post-hoc pairwise comparisons were made using Bonferroni correction, and for the number of OE, except for the non-significant  
Figure 4: Experimental scene.  
differences between 5 and 10 dB, 10 and 15 dB, 15 and 18 dB of SNR, there were statistical differences between the other two SNR conditions. When comparing SNR \(=-5\) dB and SNR \(=5\) dB, SNR \(=10\) dB, SNR \(=15\) dB, and SNR \(=18\) dB pairwise, there were significant differences in CE, with Bonferroni \(p\)-values all less than 0.002. There were significant differences in MRT when the SNR was between \(-5\) dB and 15 dB and \(-5\) dB and 18 dB (Bonferroni \(p=0.000\)), and there was also a difference between 0 dB and 18 dB.  
In order to further investigate the characteristics of auditory attention perception in noisy environments, the perceptual data under different SNR conditions were analyzed separately. As the differences in ACPT performance under different noise conditions were not significant, the scatter plots of OE, CE, and MRT versus SNR were obtained by taking the mean values of the test results under two noise interference conditions, and then fitted using the least-squares fitting method, the perceptual characteristic curve corresponding to noise interference is obtained as shown in Figure 6.  
As can be seen from Figure 6, OE and CE show a logarithmic decrease with the increase in SNR, while MRT decreases exponentially with the increase in SNR. When the SNR is small, the three decrease faster, and the declining trend slows down significantly when the SNR increases to a certain extent. OE and CE are close to the value in the noiseless  
Figure 5: Influence of noise type on ACPT: (**a**) OE and CE; (**b**) MRT.  
Figure 6: Perception of ACPT in noise environment: (**a**) OE and CE; (**b**) MRT.  
condition at SNR = 18 dB, and MRT is close to the value in the noiseless condition at SNR = 15 dB. The reason may be that when the SNR reaches a certain threshold, the participants' auditory attention is focused on specific stimuli, while actively suppressing environmental interference, such as noise.  
The fitting formulas are shown in Equations (1)-(3):  
\[\text{OE}=14.857-3.171\text{ln (SNR}+6),\text{R}^{2}=0.96, \tag{1}\]  
\[\text{CE}=5.519-0.851\text{ln (SNR}+6),\text{R}^{2}=0.91, \tag{2}\]  
\[\text{MRT}=835.09-15.71\text{ln (SNR}+6),\text{R}^{2}=0.93, \tag{3}\]  
where SNR represents the signal-to-noise ratio, R\({}^{2}\) is the coefficient of determination. When only noise interference exists, the above-fitted curves can be used directly to predict auditory sustained attention perception based on the actual measured values.