## 4 Discussion  
It has been demonstrated that the level of sound pressure can increase as the crowd density increases. However, evidence of how the crowd density changes the sound field and whether the conversation behavior of users can influence the sound field has not been found in previous studies [27; 64]. In fact, the number of talkers will also increase when crowd density increases. However, the issue of whether the number of talkers can affect the sound pressure level has not been determined  
Figure 9: The influence of commercial function: (**a**) the relationship between crowd density and the number of talkers; (**b**) the relationship between crowd density and sound pressure level; (**c**) the relationship between crowd density and loudness; (**d**) the relationship between crowd density and acoustic comfort. prior to this study. Thus, in this section, we discuss some statistical methods that were used to determine the effect. First, a Pearson's correlation analysis was used to calculate the relationship between the number of talkers and the level of the sound pressure, and a two-tail \(t\)-test was used to test the significance of the difference. As Table 5 shows, the results demonstrated a positive association between the number of talkers and the sound pressure level (\(p<0.001\)). As the number of talkers increases, the level of sound pressure also increases. Secondly, we also attempted to use a linear regression to explain the relationship between the number of talkers and sound pressure level. The value of \(R^{2}\) in the regressions ranged from 0.292-0.520 (\(p<0.001\)), which meant that some models were not fit to explain the relationship between the variables accurately [71; 72]. Thus, a crosstalk analysis was used to explain the correlation extent and a chi-square test was used to test the significance of the difference. Cross-tabulation presents a table in matrix form that displays the frequency distribution of the variables. A crosstalk was used to examine the correlations between survey data based on cross-tabulation [73]. In Table 6, as the number of talkers increased, the data in the range of 68-70 dBA and 70-72 dBA followed a decreasing trend, while the data in the range of 72-74 dBA and 74-76 dBA followed an increasing trend (\(p<0.001\)). When the number of talkers increased from 0-10 persons to 10-20 persons, the data decreased by 16.0% in the range of 68-70 dBA and 70-72 dBA, and increased 16.0% in the range of 72-74 dBA and 74-76 dBA. When the number of talkers reached 30-40 persons, the level of the sound pressure did not increase because 72.0% of data focused on the range of 72-74 dBA, and only 20.0% of the data reached the range of 74-76 dBA. In order to analyze the influence factors of acoustic comfort, a multiple logistic regression analysis was used to establish the relationship among acoustic comfort and other factors, including shop openness, season, commercial function, crowd density, sound pressure level, and the number of talkers, as shown in Table 7. The results indicated that some factors, such as shop openness, commercial function, and crowd density, were significantly correlated with acoustic comfort (\(p<0.001\)), while there was no significant influence on the acoustic comfort from the season, number of talkers, sound pressure level, and loudness (\(p>0.1\)).