Automatic acquistion of language model based on head-dependent relation between words

Seungmi Lee, Key-Sun Choi
1998 Proceedings of the 36th annual meeting on Association for Computational Linguistics -  
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
more » ... . Our experiments show that the proposed model performs better than n-gram models at 11% to 11.5~ reductions in test corpus entropy.
doi:10.3115/980845.980966 dblp:conf/acl/LeeC98 fatcat:drynrli375gsjbjuceclgrnnfi