Deeper Machine Translation and Evaluation for German

Eleftherios Avramidis, Vivien Macketanz, Aljoscha Burchardt, Jindrich Helcl, Hans Uszkoreit

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract / Description of output

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 “test suite” 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.
Original languageEnglish
Title of host publicationProceedings of the 2nd Deep Machine Translation Workshop
Place of PublicationLisbon, Portugal
PublisherÚFAL MFF UK
Pages29-38
Number of pages10
ISBN (Electronic)978-80-88132-02-8
Publication statusPublished - 21 Oct 2016
EventDeep Machine Translation Workshop 2016 - Lisboa, Portugal
Duration: 21 Oct 201621 Oct 2016
http://deepmt2016.di.fc.ul.pt/

Workshop

WorkshopDeep Machine Translation Workshop 2016
Abbreviated titleDMTW 2016
Country/TerritoryPortugal
CityLisboa
Period21/10/1621/10/16
Internet address

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