Approaches to text processing that rely on parsing the text with a context-free grammar tend to be slow and error-prone because of the massive ambiguity of long sentences. In cont...
Douglas E. Appelt, Jerry R. Hobbs, John Bear, Davi...
Abstract. This paper describes an example-based machine translation (EBMT) method based on tree-string correspondence (TSC) and statistical generation. In this method, the translat...
Abstract. The purpose of this paper is (1) to provide a theoretical justification for the use of Monte-Carlo sampling for approximate resolution of NP-hard maximization problems in...
This paper presents a direct word reordering model with novel syntax-based features for statistical machine translation. Reordering models address the problem of reordering source...
Long distance word reordering is a major challenge in statistical machine translation research. Previous work has shown using source syntactic trees is an effective way to tackle ...