Abstract—In this paper, we investigate the effect of the mother language (L1) on the rhythm of a second spoken language (L2) uttered by non-native speakers. Rhythm metrics are used to analyze this effect on non-native Arabic language speech data using a Modern Standard Arabic corpus, namely the Linguistic Data Consortium West Point corpus. A common problem with available Arabic corpora is that they usually are not time-labeled because of the time-consuming nature of such a task or because of a lack of resources. This is especially problematic if we are interested in studying rhythm metrics. To cope with this problem, we propose a framework for automatically labeling corpora using parallel processing. Such labeling allows us to perform a quantitative analysis of the rhythm of Arabic. Results show the effectiveness of acoustic rhythm metrics in analyzing variable duration patterns observed in the pronunciation of L1/L2 Arabic.