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Assessing multilingual multimodal image description: Studies of native speaker preferences and translator choices

Published online by Cambridge University Press:  23 April 2018

STELLA FRANK ,
DESMOND ELLIOTT  and
LUCIA SPECIA
STELLA FRANK
Affiliation:
Centre for Language Evolution, University of Edinburgh, Edinburgh, UK e-mail: stella.frank@ed.ac.uk
DESMOND ELLIOTT
Affiliation:
Institute of Language, Cognition and Computation, University of Edinburgh, Edinburgh, UK e-mail: d.elliott@ed.ac.uk
LUCIA SPECIA
Affiliation:
Department of Computer Science, University of Sheffield, Sheffield, UK e-mail: l.specia@sheffield.ac.uk
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Abstract

Two studies on multilingual multimodal image description provide empirical evidence towards two questions at the core of the task: (i) whether target language speakers prefer descriptions generated directly in their native language, as compared to descriptions translated from a different language; (ii) whether images improve human translation of descriptions. These results provide guidance for future work in multimodal natural language processing by first showing that on the whole, translations are not distinguished from native language descriptions, and second delineating and quantifying the information gained from the image during the human translation task.

Type
Articles
Information
Natural Language Engineering , Volume 24 , Special Issue 3: Language for Images , May 2018 , pp. 393 - 413
Copyright
Copyright © Cambridge University Press 2018 

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