Hypothesis

The faculty member participating in this project has developed an Arabic POS tagger
using a combination of language rules and statistics (Khoja 2001). The Arabic tagger uses
Hidden Markov Models (HMM’s) along with the Viterbi algorithm. This tagger achieves
an accuracy of 94%.

Current research has shown that neural network taggers may achieve a better accuracy
rate than HMM taggers (Schmid, 99). We want to test this hypothesis on the Arabic
language.

It has also been shown that tagging some text with multiple taggers improves the tagging
results (Wu, 97). We will be testing this theory on Arabic by comparing the results of
tagging the same text with both the statistical POS tagger and the neural network tagger
that we will develop for this project.