Deeper Machine Translation and Evaluation for German

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F16%3A10372124" target="_blank" >RIV/00216208:11320/16:10372124 - isvavai.cz</a>

Result on the web

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DOI - Digital Object Identifier

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Result language

angličtina

Original language name

Deeper Machine Translation and Evaluation for German

Original language description

This paper describes a hybrid Machine Translation (MT) system built for translating from English to German in the domain of technical documentation. The system is based on three different MT engines (phrase-based SMT, RBMT, neural) that are joined by a selection mechanism that uses deep linguistic features within a machine learning process. It also presents a detailed source-driven manual error analysis we have performed using a dedicated &quot;test suite&quot; that contains selected examples of relevant phenomena. While automatic scores show huge differences between the engines, the overall average number or errors they (do not) make is very similar for all systems. However, the detailed error breakdown shows that the systems behave very differently concerning the various phenomena.

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

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OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

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Continuities

R - Projekt Ramcoveho programu EK

Publication year

2016

Confidentiality

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

Article name in the collection

Proceedings of the 2nd Deep Machine Translation Workshop

ISBN

978-80-88132-02-8

ISSN

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e-ISSN

neuvedeno

Number of pages

10

Pages from-to

29-38

Publisher name

ÚFAL MFF UK

Place of publication

Praha, Czechia

Event location

Lisboa, Portugal

Event date

Oct 21, 2016

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

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