Statistical Machine Translation of Subtitles: From OpenSubtitles to TED

In this paper, we describe how the differences between subtitle corpora, OpenSubtitles and TED, influence machine translation quality. In particular, we investigate whether statistical machine translation systems built on their basis can be used interchangeably. Our results show that OpenSubtiles and TED contain very different kinds of subtitles that warrant a subclassification of the genre. In addition, we have taken a closer look at the translation of questions as a sentence type with special word order. Interestingly, we found the BLEU scores for questions to be higher than for random sentences. DOI: https://doi.org/10.1007/978-3-642-40722-2_14 Posted at the Zurich Open Repository and Archive, University of Zurich ZORA URL: https://doi.org/10.5167/uzh-82233 Accepted Version Originally published at: Müller, Mathias; Volk, Martin (2013). Statistical machine translation of subtitles: From OpenSubtitles to TED. In: Gurevych, Iryna; Biemann, Chris; Zesch, Torsten. Language Processing and Knowledge in the Web. Berlin Heidelberg: Springer, 132-138. DOI: https://doi.org/10.1007/978-3-642-40722-2_14 Statistical Machine Translation of Subtitles: From OpenSubtitles to TED Mathias Müller and Martin Volk Institute of Computational Linguistics, Zurich, Switzerland Abstract. In this paper, we describe how the differences between subtitle corpora, OpenSubtitles and TED, influence machine translation quality. In particular, we investigate whether statistical machine translation systems built on their basis can be used interchangeably. Our results show that OpenSubtiles and TED contain very different kinds of subtitles that warrant a subclassification of the genre. In addition, we have taken a closer look at the translation of questions as a sentence type with special word order. Interestingly, we found the BLEU scores for questions to be higher than for random sentences. In this paper, we describe how the differences between subtitle corpora, OpenSubtitles and TED, influence machine translation quality. In particular, we investigate whether statistical machine translation systems built on their basis can be used interchangeably. Our results show that OpenSubtiles and TED contain very different kinds of subtitles that warrant a subclassification of the genre. In addition, we have taken a closer look at the translation of questions as a sentence type with special word order. Interestingly, we found the BLEU scores for questions to be higher than for random sentences.