- Muhammad Abdul-Mageed, Mona T. Diab, Sandra Kübler. 2013. ASMA: A System for Automatic Segmentation and Morpho-Syntactic Disambiguation of Modern Standard Arabic. Abstract: In this paper, we present ASMA, a fast and efficient system for automatic segmentation and fine grained part of speech (POS) tagging of Modern Standard Arabic (MSA). ASMA performs segmentation both of agglutinative and of inflectional morphological boundaries within a word. In this work, we compare ASMA to two state of the art suites of MSA tools: AMIRA 2.1 (Diab et al., 2007; Diab, 2009) and MADA+TOKAN 3.2. (Habash et al., 2009). ASMA achieves comparable results to these two systems’ state-of-theart performance. ASMA yields an accuracy of 98.34% for segmentation, and an accuracy of 96.26% for POS tagging with ar ich tagset and 97.59% accuracy with an extremely reduced tagset. 1I ntroduction
