Automatic Acquisition of Language Model based on Head-Dependent Relation between Words

Language modeling is to associate a sequence of words with a priori probability, which is a key part of many natural language applications such as speech recognition and statistical machine translation. In this paper, we present a language modeling based on a kind of simple dependency grammar. The grammar consists of head-dependent relations between words and can be learned automatically from a raw corpus using the reestimation algorithm which is also introduced in this paper. Our experiments show that the proposed model performs better than

• Type: Conference
• Year: 1998
• Where: ACL
• Authors: Seungmi Lee, Key-Sun Choi
• Keywords: ACL 1998, ACL 2007, Language Modeling, Natural Language Applications, Simple Dependency Grammar