Paper ID
(Link to PDF)

Title

Author(s)

J01-2003

The Need for Accurate Alignment in Natural Language System Evaluation

Andrew Kehler; Douglas Appelt; John Bear

W01-1401

Example-based machine translation using DP-matching between work sequences

Sumita, Eiichiro

P00-1054

Lexical Transfer Using a Vector-Space Model

Eiichiro Sumita

W99-0604

Improved Alignment Models for Statistical Machine Translation

Franz Josef Och; Christoph Tillmann; Hermann Ney

W03-0303

Word Alignment Based on Bilingual Bracketing

Bing Zhao; Stephan Vogel

J03-3004

wEBMT: Developing and Validating an Example-Based Machine Translation System using the World Wide Web

Andy Way; Nano Gough

A94-1006

Termight: Identifying and Translating Technical Terminology

Ido Dagan; Ken Church

C00-2163

A Comparison of Alignment Models for Statistical Machine Translation

Franz Josef Och; Hermann Ney

W01-1408

An Efficient A* Search Algorithm for Statistical Machine Translation

Och, Franz Josef; Ueffing, Nicola; Ney, Hermann

Quirk

Monolingual Machine Translation for Paraphrase Generation

Chris Quirk, Chris Brockett and William Dolan

W03-0309

The Duluth Word Alignment System

Bridget Thomson McInnes; Ted Pedersen

W93-0301

Robust Bilingual Word Alignment for Machine Aided Translation

Ido Dagan; Kenneth Church; Willian Gale

352_pdf_2-col

Improving IBM Word Alignment Model 1

Robert C. Moore

238_pdf_2-col

Statistical Machine Translation with Word- and Sentence-Aligned Parallel Corpora

Chris Callison-Burch, David Talbot and Miles Osborne

5-115

Improving Statistical Word Alignment with a Rule-Based Machine Translation System

Hua Wu and Haifeng Wang