Assessing multilingual multimodal image description: Studies of native speaker preferences and translator choices
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Assessing multilingual multimodal image description : Studies of native speaker preferences and translator choices. / Frank, Stella; Elliott, Desmond; Specia, Lucia.
In: Natural Language Engineering, Vol. 24, No. 3, 2018, p. 393-413.Research output: Contribution to journal › Journal article › Research › peer-review
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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