2013 · 125 citations · 29 references
Language StudiesArabicComputer ScienceArabic Morphological AnalysisComputational LinguisticsNatural Language ProcessingMachine TranslationMorphological Ambiguity ResolutionMorphological AnalysisMorphological DisambiguationMorphological ParsingPart-of-speech TaggingArabic Part-of-speech TaggingAutomatic DiacritizationDialectal Morphological AnalysisMachine Learning-based Morphological DisambiguationModern Standard ArabicMultilingual Morphological AnalysisStatistical Machine TranslationStatistical Morphological Disambiguation
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-to-English statistical machine translation. 1
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