The Arabic language is a collection of spoken dialects with important phonological, morphological, lexical, and syntactic differences, along with a standard written language, Modern Standard Arabic (MSA). Since the spoken dialects are not officially written, it is very costly to obtain adequate corpora to use for training dialect NLP tools such as parsers. In this paper, we address the problem of parsing transcribed spoken Levantine Arabic (LA). We do not assume the existence of any annotated LA corpus (except for development and testing), nor of a parallel corpus LA-MSA. Instead, we use explicit knowledge about the relation between LA and MSA.
Chiang et al. REF highlighted this problem of parsing dialect language vs the Modern Standard Arabic (MSA).
Parsing Arabic Dialects
Conference Of The European Association For Computational Linguistics
Computer Science