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Combining data-driven MT systems for improved sign language translation

Creator:

Morrissey, Sara; Way, Andy; Stein, Daniel; Bungeroth, Jan; Ney, Hermann;

Institution: European Association for Machine Translation
Subject Keywords: Machine translating; sign language translation;
Region:
Description:

In this paper, we investigate the feasibility of combining two data-driven machine translation (MT) systems for the translation of sign languages (SLs). We take the MT systems of two prominent data-driven research groups, the MaTrEx system developed at DCU and the Statistical Machine
Translation (SMT) system developed at RWTH Aachen University, and apply their respective approaches to the task of translating Irish Sign Language and German Sign Language into English and German. In a set of experiments supported by automatic evaluation results, we show that
there is a definite value to the prospective merging of MaTrEx’s Example-Based MT chunks and distortion limit increase with RWTH’s constraint reordering.

Format:

application/pdf

Related: http://doras.dcu.ie/15229/1/MorrisseyEtAl_summit_07.pdf
Suggested citation:

Morrissey, Sara; Way, Andy; Stein, Daniel; Bungeroth, Jan; Ney, Hermann; . () Combining data-driven MT systems for improved sign language translation [Online]. Available from: http://publichealthwell.ie/node/624089 [Accessed: 17th October 2019].

  

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