A survey on Sign Language machine translation

Sign Languages (SLs) are employed by deaf and hard-of-hearing (DHH) people to communicate on a daily basis. However, the communication with hearing people still faces some barriers, mainly because of the scarce knowledge about SLs among hearing people. Hence, tools to allow the communication between users of either sign or spoken languages must be encouraged. A stepping stone in this direction is the research of the sign language translation (SLT) task, which aims to produce a spoken language translation of a sign language video or vice versa. By implementing these types of translators in portable devices, we will make considerable progress towards a barrier-free communication between DHH and hearing people. That is why, in this work, we focus on reviewing the literature on SLT and provide the necessary background about SLs. Besides, we summarise the available datasets and the results found in the literature for one of the most used datasets, the RWTH-PHOENIX-2014T. Moreover, the survey lists the challenges that need to be tackled within the SLT research and also for the adoption of SLT technologies, and proposes future research lines. •A survey on the sign language machine translation task.•An extensive review on traditional and neural sign language translation systems.•Results from the literature for the RWTH-PHOENIX-2014T dataset are provided.•Sign language translation datasets are summarised.•Sign language translation challenges and future lines of research are analysed.