Search Results for author: Aljoscha Burchardt

Found 20 papers, 2 papers with code

A Linguistically Motivated Test Suite to Semi-Automatically Evaluate German–English Machine Translation Output

1 code implementation LREC 2022 Vivien Macketanz, Eleftherios Avramidis, Aljoscha Burchardt, He Wang, Renlong Ai, Shushen Manakhimova, Ursula Strohriegel, Sebastian Möller, Hans Uszkoreit

Furthermore, we present various exemplary applications of our test suite that have been implemented in the past years, like contributions to the Conference of Machine Translation, the usage of the test suite and MT outputs for quality estimation, and the expansion of the test suite to the language pair Portuguese–English.

Machine Translation

When Performance is not Enough -- A Multidisciplinary View on Clinical Decision Support

no code implementations27 Apr 2022 Roland Roller, Klemens Budde, Aljoscha Burchardt, Peter Dabrock, Sebastian Möller, Bilgin Osmanodja, Simon Ronicke, David Samhammer, Sven Schmeier

Scientific publications about machine learning in healthcare are often about implementing novel methods and boosting the performance - at least from a computer science perspective.

BIG-bench Machine Learning

Fine-grained linguistic evaluation for state-of-the-art Machine Translation

no code implementations WMT (EMNLP) 2020 Eleftherios Avramidis, Vivien Macketanz, Ursula Strohriegel, Aljoscha Burchardt, Sebastian Möller

This paper describes a test suite submission providing detailed statistics of linguistic performance for the state-of-the-art German-English systems of the Fifth Conference of Machine Translation (WMT20).

Machine Translation Translation

Evaluating Machine Translation in a Usage Scenario

no code implementations LREC 2016 Rosa Gaudio, Aljoscha Burchardt, Ant{\'o}nio Branco

In this document we report on a user-scenario-based evaluation aiming at assessing the performance of machine translation (MT) systems in a real context of use.

Machine Translation Translation

The taraX\"U corpus of human-annotated machine translations

no code implementations LREC 2014 Eleftherios Avramidis, Aljoscha Burchardt, Sabine Hunsicker, Maja Popovi{\'c}, Cindy Tscherwinka, David Vilar, Hans Uszkoreit

Human translators are the key to evaluating machine translation (MT) quality and also to addressing the so far unanswered question when and how to use MT in professional translation workflows.

General Classification Machine Translation +1

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