We are interested in diacritizing Semitic languages, especially Syriac, using only diacritized texts. Previous methods have required the use of tools such as part-of-speech tagger...
We define a probabilistic morphological analyzer using a data-driven approach for Syriac in order to facilitate the creation of an annotated corpus. Syriac is an under-resourced S...
Peter McClanahan, George Busby, Robbie Haertel, Kr...
We present MAGEAD, a morphological analyzer and generator for the Arabic language family. Our work is novel in that it explicitly addresses the need for processing the morphology ...
We discuss a named entity recognition system for Arabic, and show how we incorporated the information provided by MADA, a full morphological tagger which uses a morphological anal...
Benjamin Farber, Dayne Freitag, Nizar Habash, Owen...
We propose a novel lexicon acquirer that works in concert with the morphological analyzer and has the ability to run in online mode. Every time a sentence is analyzed, it detects ...
This paper describes a method based on morphological analysis of words for a Persian Part-Of-Speech (POS) tagging system. This is a main part of a process for expanding a large Pe...
Morphological analyzers and part-of-speech taggers are key technologies for most text analysis applications. Our aim is to develop a part-of-speech tagger for annotating a wide ra...
Resource-poor languages may suffer from a lack of any of the basic resources that are fundamental to computational linguistics, including an adequate digital lexicon. Given the re...
MAGEAD is a morphological analyzer and generator for Modern Standard Arabic (MSA) and its dialects. We introduced MAGEAD in previous work with an implementation of MSA and Levanti...
In this paper we use statistical machine translation and morphology information from two different morphological analyzers to try to improve translation quality by linguistically ...