Morphological Analysis and Disambiguation for Dialectal Arabic
نویسندگان
چکیده
The many differences between Dialectal Arabic and Modern Standard Arabic (MSA) pose a challenge to the majority of Arabic natural language processing tools, which are designed for MSA. In this paper, we retarget an existing state-of-the-art MSA morphological tagger to Egyptian Arabic (ARZ). Our evaluation demonstrates that our ARZ morphology tagger outperforms its MSA variant on ARZ input in terms of accuracy in part-of-speech tagging, diacritization, lemmatization and tokenization; and in terms of utility for ARZ-toEnglish statistical machine translation.
منابع مشابه
Arabic Dialect Processing Tutorial
The existence of dialects for any language constitutes a challenge for NLP in general since it adds another set of variation dimensions from a known standard. The problem is particularly interesting and challenging in Arabic and its different dialects, where the diversion from the standard could, in some linguistic views, warrant a classification as different languages. This problem would not b...
متن کاملDialectal to Standard Arabic Paraphrasing to Improve Arabic-English Statistical Machine Translation
This paper is about improving the quality of Arabic-English statistical machine translation (SMT) on dialectal Arabic text using morphological knowledge. We present a light-weight rule-based approach to producing Modern Standard Arabic (MSA) paraphrases of dialectal Arabic out-of-vocabulary (OOV) words and low frequency words. Our approach extends an existing MSA analyzer with a small number of...
متن کاملCreating Resources for Dialectal Arabic from a Single Annotation: A Case Study on Egyptian and Levantine
Arabic dialects present a special problem for natural language processing because there are few Arabic dialect resources, they have no standard orthography, and they have not been studied much. However, as more and more written dialectal Arabic is found on social media, natural language processing for Arabic dialects has become an important goal. We present a methodology for creating a morpholo...
متن کاملCamelParser: A system for Arabic Syntactic Analysis and Morphological Disambiguation
In this paper, we present CamelParser, a state-of-the-art system for Arabic syntactic dependency analysis aligned with contextually disambiguated morphological features. CamelParser uses a state-of-the-art morphological disambiguator and improves its results using syntactically driven features. The system offers a number of output formats that include basic dependency with morphological feature...
متن کاملDialectal Arabic Orthography-based Transcription
The present paper describes the experience gained at LDC in the collection and transcription of conversational dialectal Arabic. The paper will cover the following: (a) Arabic language background; (b) objectives. principles, and methodological choices of dialectal Arabic transcription, (c) design features of LDC‟s „Arabic MultiDialectal Transcription Tool‟ (AMADAT) and metalanguage transcriptio...
متن کامل