Sciweavers

38 search results - page 1 / 8
» Improving Alignments for Better Confusion Networks for Combi...
Sort
View
COLING
2008
13 years 6 months ago
Improving Alignments for Better Confusion Networks for Combining Machine Translation Systems
The state-of-the-art system combination method for machine translation (MT) is the word-based combination using confusion networks. One of the crucial steps in confusion network d...
Necip Fazil Ayan, Jing Zheng, Wen Wang
ACL
2008
13 years 6 months ago
Machine Translation System Combination using ITG-based Alignments
Given several systems' automatic translations of the same sentence, we show how to combine them into a confusion network, whose various paths represent composite translations...
Damianos Karakos, Jason Eisner, Sanjeev Khudanpur,...
ACL
2009
13 years 2 months ago
A Comparative Study of Hypothesis Alignment and its Improvement for Machine Translation System Combination
Recently confusion network decoding shows the best performance in combining outputs from multiple machine translation (MT) systems. However, overcoming different word orders prese...
Boxing Chen, Min Zhang, Haizhou Li, AiTi Aw
ACL
2007
13 years 6 months ago
Improved Word-Level System Combination for Machine Translation
Recently, confusion network decoding has been applied in machine translation system combination. Due to errors in the hypothesis alignment, decoding may result in ungrammatical co...
Antti-Veikko I. Rosti, Spyridon Matsoukas, Richard...
EMNLP
2009
13 years 2 months ago
Lattice-based System Combination for Statistical Machine Translation
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&...