@inproceedings{belles-calvera-caro-quintana-2021-audiovisual,
title = "Audiovisual Translation through {NMT} and Subtitling in the Netflix Series {`}Cable Girls{'}",
author = "Bell{\'e}s-Calvera, Luc{\'\i}a and
Caro Quintana, Roc{\'\i}o",
editor = "Mitkov, Ruslan and
Sosoni, Vilelmini and
Gigu{\`e}re, Julie Christine and
Murgolo, Elena and
Deysel, Elizabeth",
booktitle = "Proceedings of the Translation and Interpreting Technology Online Conference",
month = jul,
year = "2021",
address = "Held Online",
publisher = "INCOMA Ltd.",
url = "https://aclanthology.org/2021.triton-1.15",
pages = "142--148",
abstract = "In recent years, the emergence of streaming platforms such as Netflix, HBO or Amazon Prime Video has reshaped the field of entertainment, which increasingly relies on subtitling, dubbing or voice-over modes. However, little is known about audiovisual translation when dealing with Neural Machine Translation (NMT) engines. This work-in-progress paper seeks to examine the English subtitles of the first episode of the popular Spanish Netflix series Cable Girls and the translated version generated by Google Translate and DeepL. Such analysis will help us determine whether there are significant linguistic differences that could lead to miscomprehension or cultural shocks. To this end, the corpus compiled consists of the Spanish script, the English subtitles available in Netflix and the translated version of the script. For the analysis of the data, errors have been classified following the DQF/MQM Error typology and have been evaluated with the automatic BLEU metric. Results show that NMT engines offer good-quality translations, which in turn may benefit translators working with audiovisual entertainment resources.",
}
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<abstract>In recent years, the emergence of streaming platforms such as Netflix, HBO or Amazon Prime Video has reshaped the field of entertainment, which increasingly relies on subtitling, dubbing or voice-over modes. However, little is known about audiovisual translation when dealing with Neural Machine Translation (NMT) engines. This work-in-progress paper seeks to examine the English subtitles of the first episode of the popular Spanish Netflix series Cable Girls and the translated version generated by Google Translate and DeepL. Such analysis will help us determine whether there are significant linguistic differences that could lead to miscomprehension or cultural shocks. To this end, the corpus compiled consists of the Spanish script, the English subtitles available in Netflix and the translated version of the script. For the analysis of the data, errors have been classified following the DQF/MQM Error typology and have been evaluated with the automatic BLEU metric. Results show that NMT engines offer good-quality translations, which in turn may benefit translators working with audiovisual entertainment resources.</abstract>
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%0 Conference Proceedings
%T Audiovisual Translation through NMT and Subtitling in the Netflix Series ‘Cable Girls’
%A Bellés-Calvera, Lucía
%A Caro Quintana, Rocío
%Y Mitkov, Ruslan
%Y Sosoni, Vilelmini
%Y Giguère, Julie Christine
%Y Murgolo, Elena
%Y Deysel, Elizabeth
%S Proceedings of the Translation and Interpreting Technology Online Conference
%D 2021
%8 July
%I INCOMA Ltd.
%C Held Online
%F belles-calvera-caro-quintana-2021-audiovisual
%X In recent years, the emergence of streaming platforms such as Netflix, HBO or Amazon Prime Video has reshaped the field of entertainment, which increasingly relies on subtitling, dubbing or voice-over modes. However, little is known about audiovisual translation when dealing with Neural Machine Translation (NMT) engines. This work-in-progress paper seeks to examine the English subtitles of the first episode of the popular Spanish Netflix series Cable Girls and the translated version generated by Google Translate and DeepL. Such analysis will help us determine whether there are significant linguistic differences that could lead to miscomprehension or cultural shocks. To this end, the corpus compiled consists of the Spanish script, the English subtitles available in Netflix and the translated version of the script. For the analysis of the data, errors have been classified following the DQF/MQM Error typology and have been evaluated with the automatic BLEU metric. Results show that NMT engines offer good-quality translations, which in turn may benefit translators working with audiovisual entertainment resources.
%U https://aclanthology.org/2021.triton-1.15
%P 142-148
Markdown (Informal)
[Audiovisual Translation through NMT and Subtitling in the Netflix Series ‘Cable Girls’](https://aclanthology.org/2021.triton-1.15) (Bellés-Calvera & Caro Quintana, TRITON 2021)
ACL