Paper: Dialectal Arabic to English Machine Translation: Pivoting through Modern Standard Arabic

ACL ID N13-1036
Title Dialectal Arabic to English Machine Translation: Pivoting through Modern Standard Arabic
Venue Annual Conference of the North American Chapter of the Association for Computational Linguistics
Session Main Conference
Year 2013
Authors

Modern Standard Arabic (MSA) has a wealth of natural language processing (NLP) tools and resources. In comparison, resources for dialectal Arabic (DA), the unstandardized spo- ken varieties of Arabic, are still lacking. We present ELISSA, a machine translation (MT) system for DA to MSA. ELISSA employs a rule-based approach that relies on morpho- logical analysis, transfer rules and dictionar- ies in addition to language models to produce MSA paraphrases of DA sentences. ELISSA can be employed as a general preprocessor for DA when using MSA NLP tools. A man- ual error analysis of ELISSA?s output shows that it produces correct MSA translations over 93% of the time. Using ELISSA to produce MSA versions of DA sentences as part of an MSA-pivoting DA-to-English MT solution, improves BLEU scores ...