Papers for Relevance Assessment by Necip Fazil Ayan

Research Question: How can we use linguistic knowledge to improve word alignment systems?

Paper ID
(Link to PDF)

Title

Author(s)

E03-1086

Interactive Word Alignment for Language Engineering

Lars Ahrenberg, Magnus Merkel, Michael Petterstedt

W03-0308

TREQ-AL: A word alignment system with limited language resources

Dan Tufis; Ana-Maria Barbu; Radu Ion

P05-2022

Using Bilingual Dependencies to Align Words in English/French Parallel Corpora

Sylwia Ozdowska

P01-1067

A Syntax-based Statistical Translation Model

Kenji Yamada; Kevin Knight

45-651

Improving Word Alignment Quality using Morpho-syntactic Information

Hermann Ney and Maja Popovic

6-130

Improved Word Alignment Using a Symmetric Lexicon Model

Richard Zens, Evgeny Matusov and Hermann Ney

P05-2012

Phrase Linguistic Classification and Generalization for Improving Statistical Machine Translation

Adria de Gispert

238_pdf_2-col

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

Chris Callison-Burch, David Talbot and Miles Osborne

drabek

Improving Bitext Word Alignments via Syntax-based Reordering of English

Elliott Franco Drabek and David Yarowsky

32-618

Symmetric Word Alignments for Statistical Machine Translation

Evgeny Matusov, Richard Zens and Hermann Ney

W02-1019

Minimum Bayes-Risk Word Alignments of Bilingual Texts

Shankar Kumar; William Byrne

C00-2163

A Comparison of Alignment Models for Statistical Machine Translation

Franz Josef Och; Hermann Ney

N03-2017

Word Alignment with Cohesion Constraint

Dekang Lin; Colin Cherry

5-115

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

Hua Wu and Haifeng Wang

W99-0604

Improved Alignment Models for Statistical Machine Translation

Franz Josef Och; Christoph Tillmann; Hermann Ney