# Perception of Familiar Second Language Accents and the Role of Linguistic Background
## 3 Results
### Accent Categorization  
The results of the accent categorization task showed that listeners with a multilingual background had numerically better performances (\(M=0.87\), \(SD=0.12\)) than listeners with a bilingual background (\(M=0.84\), \(SD=0.17\)). Moreover, bilinguals and multilinguals chose the label Greece (\(M=0.87\), \(SD=0.21\); \(M=0.92\), \(SD=0.12\) respectively) to a greater extent than the label England (\(M=0.81\), \(SD=0.20\); \(M=0.81\), \(SD=0.19\) respectively). Figure 2 displays the proportion of correct responses for bilingual and multilingual listeners, and Figure 3 displays the proportion of correct responses for bilingual and multilingual listeners per talker origin. To calculate the overall performance of listeners of both linguistic backgrounds, one-sample \(t\)-tests were used against chance (i.e., 0.5) with the average correct categorization score as the dependent variable. The test showed that both bilinguals and multilinguals performed above chance (\(t=13.06\), \(df=44\), \(p<0.001\); \(t=22.58\), \(df=52\), \(p<0.001\), respectively). We applied another series of one-sample \(t\)-tests for bilingual and multilingual listeners for each of the two talker origins. The results revealed that bilinguals and multilinguals performed above chance in both conditions (bilinguals England: \(t=10.42\), \(df=44\), \(p<0.001\); bilinguals Greece: \(t=11.85\), \(df=44\), \(p<0.001\); multilinguals England: \(t=11.51\), \(df=52\), \(p<0.001\); multilinguals Greece: \(t=26.67\), \(df=52\), \(p<0.001\)). We fitted a binomial mixed-effects model in R to examine the potential differences in the identification accuracy between bilinguals and multilinguals. Response (correct/incorrect) was the dependent variable, background (bilingual/multilingual), origin (England/Greece), and their interaction served as fixed factors, while participant and item served as random factors. The results indicated no significant differences between listeners with a multilingual and a bilingual background (represented by the intercept term), signaling that both groups had similar accuracy in the task. However, the response pertaining to the origin of Greece differed significantly from the intercept term (i.e., England), manifesting greater accuracy in the identification of Greek talkers compared to English talkers. In addition, the interaction of background and origin was not significant, showing that multi  
Figure 1: Probabilities of accent rating. from bilinguals depending on whether the responses about the talkers' origin were England or Greece. Subsequent post hoc tests with the Tukey method revealed significant differences between bilingual England-bilingual Greece (\(\beta\) = 1.322, \(SE\) = 0.407, \(z\) = 3.244, \(p\) = 0.006) and multilingual England-multilingual Greece (\(\beta\) = 1.981, \(SE\) = 0.416, \(z\) = 4.757, \(p\) < 0.001); this shows that the correct identification of the Greek origin was more prevalent than the corresponding identification of the English origin in both groups. Furthermore, significant differences emerged between bilingual England-multilingual Greece (\(\beta\) = 1.293, \(SE\) = 0.433, \(z\) = 2.985, \(p\) = 0.015) and multilingual England-bilingual Greece (\(\beta\) = 2.009, \(SE\) = 0.474, \(z\) = 4.239, \(p\) = 0.001). The results of the model are shown in Table 1.  
Figure 3: Proportion of correct responses for bilingual and multilingual listeners per talker origin. The dashed line represents the chance level. Figure 2: Proportion of correct responses for bilingual and multilingual listeners. The dashed line represents the chance level. To address potential response bias, which could lead to over- or underestimation of unfamiliar accents in the categorization task, signal detection analysis (SDA) was applied. SDA distinguishes between sensitivity (\(A^{\prime}\)), measuring accuracy in accent differentiation, and bias (\(B^{\prime}\)), capturing the influence of any pre-existing bias. Both are nonparametric indices (e.g., [27]).