Sara Morrissey


Combining EBMT, SMT, TM and IR Technologies for Quality and Scale
Sandipan Dandapat | Sara Morrissey | Andy Way | Josef van Genabith
Proceedings of the Joint Workshop on Exploiting Synergies between Information Retrieval and Machine Translation (ESIRMT) and Hybrid Approaches to Machine Translation (HyTra)


Using Example-Based MT to Support Statistical MT when Translating Homogeneous Data in a Resource-Poor Setting
Sandipan Dandapat | Sara Morrissey | Andy Way | Mikel L. Forcada
Proceedings of the 15th Annual conference of the European Association for Machine Translation


Mitigating Problems in Analogy-based EBMT with SMT and vice versa: A Case Study with Named Entity Transliteration
Sandipan Dandapat | Sara Morrissey | Sudip Kumar Naskar | Harold Somers
Proceedings of the 24th Pacific Asia Conference on Language, Information and Computation


The ATIS Sign Language Corpus
Jan Bungeroth | Daniel Stein | Philippe Dreuw | Hermann Ney | Sara Morrissey | Andy Way | Lynette van Zijl
Proceedings of the Sixth International Conference on Language Resources and Evaluation (LREC'08)

Systems that automatically process sign language rely on appropriate data. We therefore present the ATIS sign language corpus that is based on the domain of air travel information. It is available for five languages, English, German, Irish sign language, German sign language and South African sign language. The corpus can be used for different tasks like automatic statistical translation and automatic sign language recognition and it allows the specific modeling of spatial references in signing space.


Combining data-driven MT systems for improved sign language translation
Sara Morrissey | Andy Way | Daniel Stein | Jan Bungeroth | Hermann Ney
Proceedings of Machine Translation Summit XI: Papers

Hand in hand: automatic sign language to English translation
Daniel Stein | Philippe Dreuw | Hermann Ney | Sara Morrissey | Andy Way
Proceedings of the 11th Conference on Theoretical and Methodological Issues in Machine Translation of Natural Languages: Papers


An Example-Based Approach to Translating Sign Language
Sara Morrissey | Andy Way
Workshop on example-based machine translation

Users of sign languages are often forced to use a language in which they have reduced competence simply because documentation in their preferred format is not available. While some research exists on translating between natural and sign languages, we present here what we believe to be the first attempt to tackle this problem using an example-based (EBMT) approach. Having obtained a set of English–Dutch Sign Language examples, we employ an approach to EBMT using the ‘Marker Hypothesis’ (Green, 1979), analogous to the successful system of (Way & Gough, 2003), (Gough & Way, 2004a) and (Gough & Way, 2004b). In a set of experiments, we show that encouragingly good translation quality may be obtained using such an approach.