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

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Standard

Assessing multilingual multimodal image description : Studies of native speaker preferences and translator choices. / Frank, Stella; Elliott, Desmond; Specia, Lucia.

I: Natural Language Engineering, Bind 24, Nr. 3, 2018, s. 393-413.

Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt

Harvard

Frank, S, Elliott, D & Specia, L 2018, 'Assessing multilingual multimodal image description: Studies of native speaker preferences and translator choices', Natural Language Engineering, bind 24, nr. 3, s. 393-413. https://doi.org/10.1017/S1351324918000074

APA

Frank, S., Elliott, D., & Specia, L. (2018). Assessing multilingual multimodal image description: Studies of native speaker preferences and translator choices. Natural Language Engineering, 24(3), 393-413. https://doi.org/10.1017/S1351324918000074

Vancouver

Frank S, Elliott D, Specia L. Assessing multilingual multimodal image description: Studies of native speaker preferences and translator choices. Natural Language Engineering. 2018;24(3):393-413. https://doi.org/10.1017/S1351324918000074

Author

Frank, Stella ; Elliott, Desmond ; Specia, Lucia. / Assessing multilingual multimodal image description : Studies of native speaker preferences and translator choices. I: Natural Language Engineering. 2018 ; Bind 24, Nr. 3. s. 393-413.

Bibtex

@article{97679d5d05a74c04a9e01b36f42bf8bb,
title = "Assessing multilingual multimodal image description: Studies of native speaker preferences and translator choices",
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.",
author = "Stella Frank and Desmond Elliott and Lucia Specia",
year = "2018",
doi = "10.1017/S1351324918000074",
language = "English",
volume = "24",
pages = "393--413",
journal = "Natural Language Engineering",
issn = "1351-3249",
publisher = "Cambridge University Press",
number = "3",

}

RIS

TY - JOUR

T1 - Assessing multilingual multimodal image description

T2 - Studies of native speaker preferences and translator choices

AU - Frank, Stella

AU - Elliott, Desmond

AU - Specia, Lucia

PY - 2018

Y1 - 2018

N2 - 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.

AB - 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.

U2 - 10.1017/S1351324918000074

DO - 10.1017/S1351324918000074

M3 - Journal article

VL - 24

SP - 393

EP - 413

JO - Natural Language Engineering

JF - Natural Language Engineering

SN - 1351-3249

IS - 3

ER -

ID: 230797269