• Machine Translation Evaluation

    In this project, my team and I have explored using different levels of linguistic representations to improve Machine Translation Evaluation. We have looked at combining discourse trees, semantics and syntax to improve the state-of-the-art. We have used both structured (trees) and distributed (vector) representations to perform this task. Currently, we're looking at how humans evaluate translations using eyetracking.
  • Meeting and Lecture Translation

    The meeting and lecture translation project aims to tackle the challenges of spoken translation in spontaneous situations where there are: 1) multiple speakers (meetings) and 2) single speakers but highly technical content (lectures).
  • News Translation and Media Monitoring

    This project has been to translate written and spoken news, with a focus on Arabic media. Recently, we partnered with several European partners to participate in the EU H2020 SUMMA Project.
  • Machine Translation Optimization

    In this project, we looked at different aspects of MT Parameter optimization. More specifically how the choice of an optimizer and optimization metric can influence the end-to-end performance.