Improvement of a Whole Sentence Maximum Entropy Language Model Using Grammatical Features

In this paper, we propose adding long-term grammatical information in a Whole Sentence Maximun Entropy Language Model (WSME) in order to improve the performance of the model. The grammatical information was added to the WSME model as features and were obtained from a Stochastic Context-Free grammar. Finally, experiments using a part of the Penn Treebank corpus were carried out and significant improvements were acheived.

• Type: Conference
• Year: 2001
• Where: ACL
• Authors: Fredy A. Amaya, José-Miguel Benedí
• Keywords: ACL 2001, ACL 2007, Entropy Language Model, Grammatical Information, Long-term Grammatical Information