Increasing Coverage of Translation Memories with Linguistically Motivated Segment Combination Methods

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F15%3A00081035" target="_blank" >RIV/00216224:14330/15:00081035 - isvavai.cz</a>

Výsledek na webu

<a href="http://rgcl.wlv.ac.uk/events/NLP4TM/3_Paper.pdf" target="_blank" >http://rgcl.wlv.ac.uk/events/NLP4TM/3_Paper.pdf</a>

DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Increasing Coverage of Translation Memories with Linguistically Motivated Segment Combination Methods

Popis výsledku v původním jazyce

Translation memories (TMs) used in computer-aided translation (CAT) systems are the highest-quality source of parallel texts since they consist of segment translation pairs approved by professional human translators. The obvious problem is their size andcoverage of new document segments when compared with other parallel data. In this paper, we describe several methods for expanding translation memories using linguistically motivated segment combining approaches concentrated on preserving the high translational quality. The evaluation of the methods was done on a medium-size real-world translation memory and documents provided by a Czech translation company as well as on a large publicly available DGT translation memory published by European Commission. The asset of the TM expansion methods were evaluated by the pre-translation analysis of widely used MemoQ CAT system and the METEOR metric was used for measuring the quality of fully expanded new translation segments.

Název v anglickém jazyce

Increasing Coverage of Translation Memories with Linguistically Motivated Segment Combination Methods

Popis výsledku anglicky

Translation memories (TMs) used in computer-aided translation (CAT) systems are the highest-quality source of parallel texts since they consist of segment translation pairs approved by professional human translators. The obvious problem is their size andcoverage of new document segments when compared with other parallel data. In this paper, we describe several methods for expanding translation memories using linguistically motivated segment combining approaches concentrated on preserving the high translational quality. The evaluation of the methods was done on a medium-size real-world translation memory and documents provided by a Czech translation company as well as on a large publicly available DGT translation memory published by European Commission. The asset of the TM expansion methods were evaluated by the pre-translation analysis of widely used MemoQ CAT system and the METEOR metric was used for measuring the quality of fully expanded new translation segments.

Druh

D - Stať ve sborníku

CEP obor

IN - Informatika

OECD FORD obor

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Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2015

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Proceedings of The Workshop on Natural Language Processing for Translation Memories (NLP4TM)

ISBN

9789544520328

ISSN

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e-ISSN

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Počet stran výsledku

5

Strana od-do

31-35

Název nakladatele

INCOMA Ltd. Shoumen

Místo vydání

Bulgaria

Místo konání akce

Hissar, Bulgaria

Datum konání akce

1. 1. 2015

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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