Publication - Words Reordering based on Statistical Language Model

Words Reordering based on Statistical Language Model

Research Area:  
In Proceedings


Year: 2006
Authors: Theologos Athanaselis; Stylianos Bakamidis; Ioannis Dologlou
Volume: 12
Book title: Proceedings of the Transactions on Engineering, Computing and Technology
Pages: 270-273
Address: Vienna, Austria
There are multiple reasons to expect that detecting the word order errors in a text will be a difficult problem, and detection rates reported in the literature are in fact low. Although grammatical rules constructed by computer linguists improve the performance of grammar checker in word order diagnosis, the repairing task is still very difficult. This paper presents an approach for repairing word order errors in English text by reordering words in a sentence and choosing the version that maximizes the number of trigram hits according to a language model. The novelty of this method concerns the use of an efficient confusion matrix technique for reordering the words. The comparative advantage of this method is that works with a large set of words, and avoids the laborious and costly process of collecting word order errors for creating error patterns.