33.3496, Books: Sprachkontrolle im Spiegel der Maschinellen Übersetzung: Marzouk

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Wed Nov 9 21:50:51 UTC 2022


LINGUIST List: Vol-33-3496. Wed Nov 09 2022. ISSN: 1069 - 4875.

Subject: 33.3496, Books: Sprachkontrolle im Spiegel der Maschinellen Übersetzung: Marzouk

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Editor for this issue: Maria Lucero Guillen Puon <luceroguillen at linguistlist.org>
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Date: Wed, 09 Nov 2022 21:50:19
From: Sebastian Nordhoff [Sebastian.Nordhoff at langsci-press.org]
Subject: Sprachkontrolle im Spiegel der Maschinellen Übersetzung: Marzouk

 


Title: Sprachkontrolle im Spiegel der Maschinellen Übersetzung 
Subtitle: Untersuchung zur Wechselwirkung ausgewählter Regeln der Kontrollierten
Sprache mit verschiedenen Ansätzen der Maschinellen Übersetzung 
Series Title: Translation and Multilingual Natural Language Processing  

Publication Year: 2022 
Publisher: Language Science Press
	   http://langsci-press.org
	

Book URL: https://langsci-press.org/catalog/book/371 


Author: Shaimaa Marzouk

Electronic: ISBN:  9783961103942 Pages: 696 Price: Europe EURO 0 Comment: Open Access


Abstract:

Examining the general impact of the Controlled Languages rules in the context
of Machine Translation has been an area of research for many years. The
present study focuses on the following question: How do the Controlled
Language (CL) rules impact the Machine Translation (MT) output individually?
Analyzing a German corpus-based test suite of technical texts that have been
translated into English by different MT systems, the study endeavors to answer
this question at different levels: the general impact of CL rules (rule- and
system-independent), their impact at rule level (system-independent), their
impact at system level (rule-independent), and at rule and system level. The
results of five MT systems (a rule-based system, a statistical system, two
differently constructed hybrid systems, and a neural system) are analyzed and
contrasted. For this, a mixed-methods triangulation approach that includes
error annotation, human evaluation, and automatic evaluation was applied. The
data were analyzed both qualitatively and quantitatively based on the
following parameters: number and type of MT errors, style and content quality,
and scores from two automatic evaluation metrics. In line with many studies,
the results show a general positive impact of the applied CL rules on the MT
output. However, at rule level, only four rules proved to have positive
effects on all parameters; three rules had negative effects on the parameters;
and two rules did not show any significant impact. At rule and system level,
the rules affected the MT systems differently, as expected. Some rules that
had a positive impact on earlier MT approaches did not show the same impact on
the neural MT approach. Furthermore, the neural MT delivered distinctly better
results than earlier MT approaches, namely the highest error-free, style and
content quality rates both before and after the rules application, which
indicates that the neural MT offers a promising solution that no longer
requires CL rules for improving the MT output, what in turn allows for a more
natural style.
 



Linguistic Field(s): Translation


Written In: German  (deu)

See this book announcement on our website: 
http://linguistlist.org/pubs/books/get-book.cfm?BookID=164374




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