Danmu-assisted learning through back translation

Xuemei Chen
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Abstract

Abstract Based on a new type of online data, danmu comments, this article examines the reception of the English-dubbed Chinese drama Journey to the West (Season II) . This drama was adapted from a classic Chinese novel of the same title. Studies on dubbing reception have focused on how audiences understand and appreciate dubbing products. However, this article approaches dubbing reception from the perspective of usability, conceiving reception as using translations for certain purposes. I first collected danmu comments on the dubbed version from Bilibili, the most popular danmu video-sharing website in China. A multimodal discourse analysis of these comments shows that the dubbed Journey has been used for Chinese viewers to learn English. Danmu interface functions like a “blackboard” to provide back translations for viewers, helping them better understand the English lines. By proposing the concept “ danmu -assisted learning through back translation,” this study argues that dubbed material could be useful in language learning. Such informal language learning may inspire the industry to develop a danmu -based learning software for foreign languages, which could be applied in a pedagogical setting. This article reveals new temporal features of danmu subtitling, including antecedent, concurrent, and delayed danmu translations, potentially facilitating learning in various ways. It also contributes methodologically to AVT reception studies by using danmu comments to study viewers in a naturalistic setting without researcher intervention.
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通过反向翻译的丹木辅助学习
摘要本文基于一种新型的网络数据——单目评论,考察了英译剧《西游记(第二季)》的接受情况。这部剧改编自同名中国经典小说。配音接受的研究主要集中在观众如何理解和欣赏配音产品。然而,本文从可用性的角度来探讨配音接受,认为接受是为了某种目的而使用翻译。我首先从中国最受欢迎的丹木视频分享网站哔哩哔哩上收集了丹木配音版的评论。对这些评论的多模态语篇分析表明,配音版《旅行》已经被中国观众用来学习英语。弹目界面的功能就像一块“黑板”,为观众提供反向翻译,帮助他们更好地理解英语台词。本研究提出“单目反译辅助学习”的概念,认为配音材料在语言学习中可能是有用的。这种非正式的语言学习可能会激发业界开发一种基于丹木的外语学习软件,这种软件可以应用于教学环境。本文揭示了弹幕字幕翻译的新的时间特征,包括先行翻译、并发翻译和延迟翻译,这些特征可能以各种方式促进学习。它还通过在没有研究者干预的情况下使用弹幕评论在自然环境中研究观众,为AVT接受研究提供了方法上的贡献。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
1.00
自引率
0.00%
发文量
48
审稿时长
7 weeks
期刊最新文献
Studying literary translations in periodicals Review of Wang & Sawyer (2023): Machine Learning in Translation Danmu-assisted learning through back translation Technology preparedness and translator training From classical to cosmopolitan
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