## 3 Results
### Effects of Noise and Reverberation on Auditory Sustained Attention  
The reliability test was completed for all subjects' data, and the Cronbach alpha coefficient was measured to be 0.865, indicating that the internal reliability of the experiment was good. A two-way repeated ANOVA was conducted with the total number of errors E as the dependent variable and SNR and RT as the within-subjects variables; the data were approximately normally distributed, following [PERSON]'s sphericity test (\(p>0.05\)). The results showed that SNR (F = 35.846, \(p=0.000\)) and RT (F = 9.473, \(p=0.001\)) had a significant effect on E, but there was no interaction between SNR and RT, the single factor F value SNR? RT, indicating that the effect of SNR was greater than that of RT.  
The total errors for different SNR and RT scenarios were analyzed by pairwise comparison, and it was found that E was significantly different between SNR = \(-\)5 dB, 5 dB, and 15 dB. The total number of errors at RT = 0.34 s (13.0) was significantly lower than  
Figure 8: Characteristics of auditory continuous attention perception in reverberation environment. (a) OE and CE; (b) E; (c) MRT; (d) the fitting effect of OE, CE, and E.  
RT = 1.8 s (16.1), The difference in perception data between 0.34 s and 0.76 s and between 0.76 s and 1.8 s of RT was not obvious.  
After analysis of variance, the difference in the total errors between different SNRs for each RT was significant (\(p\) = 0.000). A significant difference in the total errors between different RT was found for SNR = \(-\)5 dB (\(p\) = 0.031), and when SNR = 5 dB and 15 dB, no significant difference was found in the total errors between different RT (\(p\) = 0.145 and \(p\) = 0.225). Under a large SNR, when RT is varied within a suitable range, speech intelligibility value remains high [32], which may be the reason why RT has almost no effect on the number of errors of participants under a large SNR.  
The perceptual relationship between the total number of errors, SNR, and RT was obtained through the listening experiments, and Figure 9 shows the variation of E with both in a two-dimensional distribution.  
From the above figure, when both reverberation and noise factors exist simultaneously, the characteristics of E affected by both factors are the same as those of E affected by a single factor. Under the same SNR, the larger RT corresponds to a higher total number of errors; when RT is the same, the higher SNR corresponds to a lower total number of errors. Compared with the perceptual features of auditory sustained attention under the influence of a single factor, adding one interference condition resulted in more total errors for the subjects.  
Based on the functional relationship between E, SNR, and RT under the influence of a single interference factor, the perception model is established when the two factors act together, and multiple regression analysis is used to fit SNR and RT to obtain the functional relationship of E. The fitting formula is shown in Equation (8):  
\[\text{E}=21.985-3.867\text{ln}\ (\text{SNR}+6)+1.815\text{lnRT},\ \text{R}^{2}=0.93, \tag{8}\]  
where E represents the total errors, SNR represents the signal-to-noise ratio, and R\({}^{2}\) is the coefficient of determination.  
Figure 10 shows the fitting precision.  
Figure 9: Two-dimensional distribution of error number when noise and reverberation work together.  
The scatter points in Figure 10 are distributed near the central line, indicating a high fitting accuracy.