Papers for Relevance Assessment by Yang Liu

Research Question: Since Log-linear models have been successfully applied to statistical machine translation and proved to be a useful tool to include additional dependencies, can they be applied to word alignment and achieve solid better results than the-state-of-the-art alignment methods?

Reformulation: Can Log-linear models be applied to word alignment and achieve solid better results than the-state-of-the-art alignment methods?

Paper ID
(Link to PDF)

Title

Author(s)

6-130

Improved Word Alignment Using a Symmetric Lexicon Model

Richard Zens, Evgeny Matusov and Hermann Ney

P00-1056

Improved Statistical Alignment Models

Franz Josef Och; Hermann Ney

J04-4002

The Alignment Template Approach to Statistical Machine Translation

Franz Josef Och; Hermann Ney

H05-1010

A Discriminative Matching Approach to Word Alignment

Ben Taskar; Lacoste-Julien Simon; Klein Dan

32-618

Symmetric Word Alignments for Statistical Machine Translation

Evgeny Matusov, Richard Zens and Hermann Ney

C00-2163

A Comparison of Alignment Models for Statistical Machine Translation

Franz Josef Och; Hermann Ney

H05-1011

A Discriminative Framework for Bilingual Word Alignment

Robert C. Moore

5-115

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

Hua Wu and Haifeng Wang

H05-1096

Word-Level Confidence Estimation for Machine Translation using Phrase-Based Translation Models

Nicola Ueffing; Hermann Ney

W05-0814

ISI’s Participation in the Romanian-English Alignment Task

Alexander Fraser; Daniel Marcu

238_pdf_2-col

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

Chris Callison-Burch, David Talbot and Miles Osborne

W05-0809

Word Alignment for Languages with Scarce Resources

Joel Martin; Rada Mihalcea; Ted Pedersen

J04-2003

Statistical Machine Translation with Scarce Resources Using Morpho-syntactic Information

Sonja Nielsen and Hermann Ney

H05-1098

The Hiero Machine Translation System: Extensions, Evaluation, and Analysis

David Chiang; Adam Lopez; Nitin Madnani; Christof Monz; Philip Resnik; Michael Subotin

45-651

Improving Word Alignment Quality using Morpho-syntactic Information

Hermann Ney and Maja Popovic