Problems with automating translation of movie/TV show subtitles
This addresses challenges in automating subtitle translation for media localization, but it is incremental as it focuses on problem identification rather than novel solutions.
The paper identifies 27 problems in automating subtitle translation, categorizing them into textual translation, subtitle guidelines, and MT adaptability issues, and finds that state-of-the-art NLP systems perform poorly, requiring post-processing solutions.
We present 27 problems encountered in automating the translation of movie/TV show subtitles. We categorize each problem in one of the three categories viz. problems directly related to textual translation, problems related to subtitle creation guidelines, and problems due to adaptability of machine translation (MT) engines. We also present the findings of a translation quality evaluation experiment where we share the frequency of 16 key problems. We show that the systems working at the frontiers of Natural Language Processing do not perform well for subtitles and require some post-processing solutions for redressal of these problems