Philip Williams I am a research associate in the Institute for Language, Cognition and Computation, where I have been working in the field of machine translation since 2009. My main research interests include multilingual translation and the use of linguistic annotation for machine translation. Current Projects ELITR - European Live Translator (EU Horizon 2020 Research and Innovation Programme, Grant Agreement No 825460). Software and Data Software and datasets that I've either led the development of or made significant contributions to: OPUS-100, a massively multilingual corpus derived from OPUS. Used for the experiments in Zhang et al, (2020). WMT17 Transformer Scripts, scripts for training Transformer models in Nematus. Nematus, a toolkit for neural machine translation, written in Python and Tensorflow. Moses, a toolkit for statistical machine translation, written in C++. taco (no longer supported), a toolkit for working with unification-based constraints in SMT. This software was developed for my thesis and was used in Williams and Koehn (2011), Williams and Koehn (2014), Williams et al. (2014). Tutorials and Talks Introduction to Nematus, a lab run at the Machine Translation Marathon, Edinburgh, August 2019. Syntax-based Statistical Machine Translation, a tutorial given at EMNLP 2014 with Philipp Koehn, October 2014. Morphology in Statistical Machine Translation, a talk from the Machine Translation Marathon, September 2014. Publications Biao Zhang, Philip Williams, Ivan Titov, Rico Sennrich (2020). Improving Massively Multilingual Neural Machine Translation and Zero-Shot Translation. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics. Online, pp. 1628-1639. Dominik Macháček, Jonáš Kratochvíl, Sangeet Sagar, Matúš Žilinec, Ondřej Bojar, Thai-Son Nguyen, Felix Schneider, Philip Williams and Yuekun Yao (2020). ELITR Non-Native Speech Translation at IWSLT 2020. Proceedings of the 17th International Conference on Spoken Language Translation (IWSLT 2020), Seattle, USA. Dario Franceschini, Chiara Canton, Ivan Simonini, Armin Schweinfurth, Adelheid Glott, Sebastian Stüker, Thai-Son Nguyen, Felix Schneider, Thanh-Le Ha, Alex Waibel, Barry Haddow, Philip Williams, Rico Sennrich, Ondřej Bojar, Sangeet Sagar, Dominik Macháček, Otakar Smrž (2020). Removing European Language Barriers with Innovative Machine Translation Technology In Proceedings of the 1st International Workshop on Language Technology Platforms, Marseille, France, pp. 44-49. Joanna Wetesko, Marcin Chochowski, Pawel Przybysz, Philip Williams, Roman Grundkiewicz, Rico Sennrich, Barry Haddow, Antonio Valerio Miceli Barone, and Alexandra Birch (2019). Samsung and University of Edinburgh's System for the IWSLT 2019 In 16th International Workshop on Spoken Language Translation, Philip Williams, Marcin Chochowski, Pawel Przybysz, Rico Sennrich, Barry Haddow, and Alexandra Birch (2018). Samsung and University of Edinburgh’s System for the IWSLT 2018 Low Resource MT Task. In Proceedings of the 15th International Workshop on Spoken Language Translation, Bruges, Belgium. Rico Sennrich, Alexandra Birch, Anna Currey, Ulrich Germann, Barry Haddow, Kenneth Heafield, Antonio Valerio Miceli Barone, Philip Williams (2017). The University of Edinburgh's Neural MT Systems for WMT17 In Proceedings of the Second Conference on Machine Translation, Volume 2: Shared Task Papers. Copenhagen, Denmark. Jan-Thorsten Peter, Hermann Ney, Ondřej Bojar, Ngoc-Quan Pham, Jan Niehues, Alex Waibel, Franck Burlot, François Yvon, Mārcis Pinnis, Valters Šics, Joost Bastings, Miguel Rios, Wilker Aziz, Philip Williams, Frédéric Blain, Lucia Specia (2017) The QT21 Combined Machine Translation System for English to Latvian In proceedings of the Second Conference on Machine Translation, Volume 2: Shared Task Papers, Copenhagen, Denmark, pp. 348-357. Anne Beyer, Vivien Macketanz, Aljoscha Burchardt and Philip Williams (2017) Can Out-of-the-box NMT Beat a Domain-trained Moses on Technical Data? In Conference Proceedings EAMT 2017, Valencia, Spain, 2017. Aljoscha Burchardt, Vivien Macketanz, Jon Dehdari, Georg Heigold, Jan-Thorsten Peter, Philip Williams (2017) A Linguistic Evaluation of Rule-Based, Phrase-Based, and Neural MT Engines. In The Prague Bulletin of Mathematical Linguistics, vol. 108, no. 1, pp. 159--170. Philip Williams, Rico Sennrich, Matt Post, and Philipp Koehn (2016). Syntax-based Statistical Machine Translation Synthesis Lectures on Human Language Technologies, Morgan and Claypool. Philip Williams, Rico Sennrich, Maria Nădejde, Matthias Huck, Barry Haddow, Ondřej Bojar (2016). Edinburghʼs Statistical Machine Translation Systems for WMT16 In Proceedings of the First Conference on Machine Translation: Volume 2, Shared Task Papers. Berlin, Germany, pp. 399-410. Philip Williams, Rico Sennrich, Maria Nadejde, Matthias Huck, and Philipp Koehn (2015). Edinburghʼs Syntax-Based Systems at WMT 2015. In Proceedings of the Tenth Workshop on Statistical Machine Translation. Lisbon, Portugal, pp. 199-209. Rico Sennrich, Philip Williams, and Matthias Huck (2015). A tree does not make a well-formed sentence: Improving syntactic string-to-tree statistical machine translation with more linguistic knowledge Computer Speech & Language, Volume 32, Issue 1, Pages 27-45 Philip Williams (2014). Unification-based Constraints for Statistical Machine Translation PhD thesis, University of Edinburgh Markus Freitag, Stephan Peitz, Joern Wuebker, Hermann Ney, Matthias Huck, Rico Sennrich, Nadir Durrani, Maria Nadejde, Philip Williams, Philipp Koehn, Teresa Herrmann, Eunah Cho, and Alex Waibel (2014) EU-BRIDGE MT: Combined Machine Translation Proceedings of the Ninth Workshop on Statistical Machine Translation Philip Williams, Rico Sennrich, Maria Nadejde, Matthias Huck, Eva Hasler, and Philipp Koehn (2014). Edinburgh's Syntax-Based Systems at WMT 2014 Proceedings of the Ninth Workshop on Statistical Machine Translation Philip Williams and Philipp Koehn (2014). Using Feature Structures to Improve Verb Translation in English-to-German Statistical MT Proceedings of the 3rd Workshop on Hybrid Approaches to Machine Translation (HyTra) Maria Nadejde, Philip Williams, and Philipp Koehn (2013). Edinburgh's Syntax-Based Machine Translation Systems Proceedings of the Eighth Workshop on Statistical Machine Translation Wenduan Xu, Yue Zhang, Philip Williams, and Philipp Koehn (2013). Learning to Prune: Context-Sensitive Pruning for Syntactic MT Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics Philip Williams and Philipp Koehn (2012). GHKM Rule Extraction and Scope-3 Parsing in Moses Proceedings of the 7th Workshop on Statistical Machine Translation Philip Williams and Philipp Koehn (2011). Agreement Constraints for Statistical Machine Translation into German Proceedings of the 6th Workshop on Statistical Machine Translation Philipp Koehn, Barry Haddow, Philip Williams, and Hieu Hoang (2010). More Linguistic Annotation for Statistical Machine Translation Proceedings of the Joint 5th Workshop on Statistical Machine Translation and MetricsMATR