We propose a structure called dependency forest for statistical machine translation. A dependency forest compactly represents multiple dependency trees. We develop new algorithms ...
Zhaopeng Tu, Yang Liu, Young-Sook Hwang, Qun Liu, ...
We improve the quality of statistical machine translation (SMT) by applying models that predict word forms from their stems using extensive morphological and syntactic information...
HMM-based models are developed for the alignment of words and phrases in bitext. The models are formulated so that alignment and parameter estimation can be performed efficiently....
In this work, we model the writing revision process of English as a Second Language (ESL) students with syntaxdriven machine translation methods. We compare two approaches: tree-t...
Current system combination methods usually use confusion networks to find consensus translations among different systems. Requiring one-to-one mappings between the words in candid...
Yang Feng, Yang Liu, Haitao Mi, Qun Liu, Yajuan L&...