Papers for Relevance Assessment by Young-Sook Hwang

Research Question: Obtain less ambiguious translation pairs

Reformulation: Obtain less ambiguous translation pairs

Paper ID
(Link to PDF)

Title

Author(s)

C00-2094

Using a Probabilistic Class-Based Lexicon for Lexical Ambiguity Resolution

Detlef Prescher; Stefan Riezler; Mats Rooth

P98-2221

Modeling with Structures in Statistical Machine translation

Ye-Yi Wang; Alex Waibel

P99-1029

Using Mutual Information to Resolve Query Translation Ambiguities and Query Term Weighting

Myung-Gil Jang; Sung Hyon Myaeng; Se Young Park

Zhao

Phrase Pair Rescoring with Term Weighting for Statistical Machine Translation

Bing Zhao, Stephan Vogel, Matthias Eck and Alex Waibel

C00-2159

A Bootstrapping Method for Extracting Bilingual Text Pairs

Hiroshi Masuichi; Raymond Flournoy; Stefan Kaufmann; Stanley Peters

A83-1029

COMPUTER-ASSISTED TRANSLATION SYSTEMS: The Standard Design and A Multi-level Design

Alan K. Melby

C92-2101

LEARNING TRANSLATION TEMPLATES FROM BILINGUAL TEXT

Hiroyuki KAJI; Yuuko KIDA; Yasutsugu MORIMOTO

W00-1325

Statistical Filtering and Subcategorization Frame Acquisition

Anna Korhonen; Genevieve Gorrell; Diana McCarthy

W97-0119

Finding Terminology Translations from Non-parallel Corpora

Pascale Fu

A97-1052

Automatic Extraction of Subcategorization from Corpora

Ted Briscoe; John Carroll

W03-0310

Bootstrapping Parallel Corpora

Chris Callison-Burch; Miles Osborne

C88-1042

An Active Bilingual Lexicon for Machine Translation

Igal GOLAN; Shalom LAPPIN; Mori RIMON

W98-1114

Can Subcategorisation Probabilities Help a Statistical Parser

John Carroll; Guido Minnen; Ted Briscoe

C82-1034

MULTI-LEVEL TRANSLATION AIDS IN A DISTRIBUTED SYSTEM

Alan K. Melby

P05-1033

A Hierarchical Phrase-Based Model for Statistical Machine Translation

David Chiang