Login (DCU Staff Only)
Login (DCU Staff Only)

DORAS | DCU Research Repository

Explore open access research and scholarly works from DCU

Advanced Search

Combining semantic and syntactic generalization in example-based machine translation

Ebling, Sarah, Way, Andy orcid logoORCID: 0000-0001-5736-5930, Volk, Martin and Kumar Naskar, Sudip (2011) Combining semantic and syntactic generalization in example-based machine translation. In: The 15th conference of the European Association for Machine Translation (EAMT 2011), 30th - 31st of May 2011, Leuven, Belgium.

Abstract
In this paper, we report our experiments in combining two EBMT systems that rely on generalized templates, Marclator and CMU-EBMT, on an English–German translation task. Our goal was to see whether a statistically significant improvement could be achieved over the individual performances of these two systems. We observed that this was not the case. However, our system consistently outperformed a lexical EBMT baseline system.
Metadata
Item Type:Conference or Workshop Item (Paper)
Event Type:Conference
Refereed:Yes
Uncontrolled Keywords:Statistical Machine Translation; SMT; Example- Based Machine Translation; EBMT; Corpus-Based Machine Translation; CBMT
Subjects:Computer Science > Machine translating
DCU Faculties and Centres:Research Initiatives and Centres > Centre for Next Generation Localisation (CNGL)
DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing
Published in: Proceedings of the 15th conference of the European Association for Machine Translation. . European Association for Machine Translation.
Publisher:European Association for Machine Translation
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
ID Code:16413
Deposited On:21 Jul 2011 14:42 by Shane Harper . Last Modified 09 Nov 2018 14:29
Documents

Full text available as:

[thumbnail of Combining_Semantic_and_Syntactic_Generalization_in_Example-Based_Machine_Translation.pdf]
Preview
PDF - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
362kB
Downloads

Downloads

Downloads per month over past year

Archive Staff Only: edit this record