Building a Sign Language corpus for use in Machine Translation

In recent years data-driven methods of machine translation (MT) have overtaken rule-based approaches as the predominant means of automatically translating between languages. A pre-requisite for such an approach is a parallel corpus of the source and target languages. Technological developments in sign language (SL) capturing, analysis and processing tools now mean that SL corpora are becoming increasingly available. With transcription and language analysis tools being mainly designed and used for linguistic purposes, we describe the process of creating a multimedia parallel corpus specifically for the purposes of English to Irish Sign Language (ISL) MT. As part of our larger project on localisation, our research is focussed on developing assistive technology for patients with limited English in the domain of healthcare.
Focussing on the first point of contact a patient has with a GPís office, the medical secretary, we sought to develop a corpus from the dialogue between the two parties when scheduling an appointment. Throughout the development process we have created one parallel corpus in six different modalities from this initial dialogue, namely English speech, English text, ISL videos, Bangla text, HamNoSys transcription and SiGML code. In this paper we discuss the multi-stage process of the development of this parallel corpus as individual and interdependent entities, both for our own MT purposes and their usefulness in the wider MT and SL research domains.