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A Rhythm-Based Analysis of Arabic Native and Non-Native Speaking Styles

Soumaya Gharsellaoui 1, Adel Omar Dahmane 1, Yousef Alotaibi 2, Sid Ahmed Selouani 3, Alaidine Ben Ayed 3, and Yacine Benahmed 3
1. UQTR University, Electrical and computer engineering department, Trois-Rivières, Canada
2. King Saud University, Department of computer engineering, Riyadh, Saudi Arabia
3. Université de Moncton, Campus de Shippagan, New Brunswick, Canada
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.

Index Terms—rhythm, metrics, modern standard arabic, non-native speech, parallel automatic labeling

Cite: Soumaya Gharsellaoui, Adel Omar Dahmane, Yousef Alotaibi, Sid Ahmed Selouani, Alaidine Ben Ayed, and Yacine Benahmed, "A Rhythm-Based Analysis of Arabic Native and Non-Native Speaking Styles," International Journal of Signal Processing Systems, Vol. 1, No. 2, pp. 202-207, December 2013. doi: 10.12720/ijsps.1.2.202-207

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