ABSTRACT
A Word-Tag Model (WTM) is a generalization of the Word N-Gram (WNG) model. It assigns syntactic tags to each of the candidate words and treats the word sequence as a Hidden Markov Model (HMM). The probability of the word is now a function of only the tag, and the system searches for the word-tag sequence that has maximum probability.
