An Open-Source Gloss-Based Baseline for Spoken to Signed Language
  Translation
Amit Moryossef Mathias Müller Anne Göhring Zifan Jiang Yoav Goldberg Sarah Ebling
Sign language translation systems are complex and require many components. As
a result, it is very hard to compare methods across publications. We present an
open-source implementation of a text-to-gloss-to-pose-to-video pipeline
approach, demonstrating conversion from German to Swiss German Sign Language,
French to French Sign Language of Switzerland, and Italian to Italian Sign
Language of Switzerland. We propose three different components for the
text-to-gloss translation: a lemmatizer, a rule-based word reordering and
dropping component, and a neural machine translation system. Gloss-to-pose
conversion occurs using data from a lexicon for three different signed
languages, with skeletal poses extracted from videos. To generate a sentence,
the text-to-gloss system is first run, and the pose representations of the
resulting signs are stitched together.