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  • This paper examines two techniques of manual evaluation that can be used to identify error types of individual machine translation systems. The first technique of %22blind post-editing%22 is being used in WMT evaluation campaigns since 2009 and manually constructed data of this type are available for various language pairs. The second technique of explicit marking of errors has been used in the past as well. We propose a method for interpreting blind post-editing data at a finer level and compare the results with explicit marking of errors. While the human annotation of either of the techniques is not exactly reproducible (relatively low agreement), both techniques lead to similar observations of differences of the systems. Specifically, we are able to suggest which errors in MT output are easy and hard to correct with no access to the source, a situation experienced by users who do not understand the source language.
  • This paper examines two techniques of manual evaluation that can be used to identify error types of individual machine translation systems. The first technique of %22blind post-editing%22 is being used in WMT evaluation campaigns since 2009 and manually constructed data of this type are available for various language pairs. The second technique of explicit marking of errors has been used in the past as well. We propose a method for interpreting blind post-editing data at a finer level and compare the results with explicit marking of errors. While the human annotation of either of the techniques is not exactly reproducible (relatively low agreement), both techniques lead to similar observations of differences of the systems. Specifically, we are able to suggest which errors in MT output are easy and hard to correct with no access to the source, a situation experienced by users who do not understand the source language. (en)
Title
  • Analyzing Error Types in English-Czech Machine Translation
  • Analyzing Error Types in English-Czech Machine Translation (en)
skos:prefLabel
  • Analyzing Error Types in English-Czech Machine Translation
  • Analyzing Error Types in English-Czech Machine Translation (en)
skos:notation
  • RIV/00216208:11320/11:10107805!RIV12-GA0-11320___
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(7E09003), P(GAP406/11/1499), P(GPP406/10/P259)
http://linked.open...iv/cisloPeriodika
  • 1
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
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http://linked.open...iv/duvernostUdaju
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http://linked.open...dnocenehoVysledku
  • 186206
http://linked.open...ai/riv/idVysledku
  • RIV/00216208:11320/11:10107805
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • translation; machine; czech; english; types; error; analyzing (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...odStatuVydavatele
  • CZ - Česká republika
http://linked.open...ontrolniKodProRIV
  • [E883914E9F9D]
http://linked.open...i/riv/nazevZdroje
  • The Prague Bulletin of Mathematical Linguistics
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...vavai/riv/projekt
http://linked.open...UplatneniVysledku
http://linked.open...v/svazekPeriodika
  • 95
http://linked.open...iv/tvurceVysledku
  • Bojar, Ondřej
issn
  • 0032-6585
number of pages
http://bibframe.org/vocab/doi
  • 10.2478/v10108-011-0005-2
http://localhost/t...ganizacniJednotka
  • 11320
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