Cross-Dialectal Arabic Processing

Abstract

Abstract. We present, in this paper an Arabic multi-dialect study including dialects from both the Maghreb and the Middle-east that we compare to the Modern Standard Arabic (MSA). Three dialects from Maghreb are concerned by this study: two from Algeria and one from Tunisia and two dialects from Middle-east (Syria and Palestine). The resources which have been built from scratch have lead to a collection of a multi-dialect parallel resource. Furthermore, this collection has been aligned by hand with a MSA corpus. We conducted several analytical studies in order to understand the relationship between these vernacular languages. For this, we studied the closeness between all the pairs of dialects and MSA in terms of Hellinger distance. We also performed an experiment of dialect identification. This experiment showed that neighbouring dialects as expected tend to be confused, making difficult their identification. Because the Arabic dialects are different from one region to another which make the communication between people difficult, we conducted cross-lingual machine translation between all the pairs of dialects and also with MSA. Several interesting conclusions have been carried out from this experiment.

A Conventional Orthography for Algerian Arabic

“…In the same way, (Harrat et al, 2015) present an Arabic multi-dialect study including dialects from both the Maghreb and the Middle-east that they compare to the Modern Standard Arabic (MSA). Three dialects from Maghreb are concerned by this study: two from Algeria : Annaba's dialect (ANB), the language spoken in the east of Algeria, on Algiers's dialect (ALG), the language used in the capital of Algeria, and one from Tunisia, on Sfax's dialect (TUN) spoken in the south of Tunisia and two dialects from Middle-east (Syria and Palestine).…”

Automatic Diacritics Restoration for Dialectal Arabic Text

“…For MSA, WER reported by their system was 16.2% and 23.1% based on the corpus in use, while DER reported was 4.1% and 5.7% based on the corpus in use. For Algiers dialect corpus, WER reported by their system was 25.8%, DER reported by their system was 12.8% [13].…”

Natural Language Processing for Dialectical Arabic: A Survey

“…) Iskra et al, 2004) (Zbib et al, 2012), (Salloum & Habash, 2011), (Jehl et al, 2012, (Salloum & Habash, 2012), (Soltau et al, 2011) (Mourad & Darwish, 2013) Syrian (Graff & Maamouri , 2012) (Harrat et al, 2015), (Sadat, Kazemi, & Farzindar, 2014) (Belgacem et al, 2010), (Lei & Hansen, 2009), ) Iskra et al, 2004) North Syrian (Sawaf, 2010) Damascus (Sawaf, 2010) Lebanese (Sadat, Kazemi, & Farzindar, 2014) ) Iskra et al, 2004) (Sawaf, 2010) Jordanian (Salloum &Habash, 2014) (Sadat, Kazemi, & Farzindar, 2014) ) Iskra et al, 2004) (Sawaf, 2010) (Duwairi et al, 2014) Palestinian (Jarrar et al, 2014) (Harrat et al, 2015), (Sadat, Kazemi, & Farzindar, 2014) (Lei & Hansen, 2009), ) Iskra et al, 2004) (Sawaf, 2010) Iraqi (Almeman & Lee, 2012) (Masmou di et al, 2015, (Darwish, 2013) (Graff et al, 2006),…”

“…annotations to identify Levantine, Gulf, Egyptian, Iraqi, and Maghrebi dialects. The identification of several Maghrebi dialects in addition to Syrian and Palestinian Arabic was an aspect in the crossdialectical study proposed in (Harrat et al, 2015).…”