Eva Hasler



Contact

I am a PhD candidate at the School of Informatics working on Statistical Machine Translation, advised by Philipp Koehn and Barry Haddow. I am interested in discriminative training methods and online learning for large-scale parameter tuning of SMT systems, as well as domain and topic adaptation techniques for machine translation. My current work is on document-level and sentence-level adaptation of translation models. I am particularly interested in dynamic adaptation scenarios where the domain of an input text has to be inferred automatically.

Before starting my PhD I worked as a software developer for the enterprise search team at Microsoft Munich.

Note: I have recently finished my PhD and joined the machine translation group at the University of Cambridge.

Publications

  • Combining Domain and Topic Adaptation for SMT, Eva Hasler, Barry Haddow, Philipp Koehn, In Proceedings of AMTA 2014.

  • UEdin: Translating L1 Phrases in L2 Context using Context-Sensitive SMT, Eva Hasler, In Proceedings of the 8th International Workshop on Semantic Evaluation (SemEval 2014). [slides][bib]

  • Dynamic Topic Adaptation for SMT using Distributional Profiles, Eva Hasler, Barry Haddow, Philipp Koehn, In Proceedings of WMT 2014. [slides][bib]

  • Edinburgh's Syntax-Based Systems at WMT 2014, Philip Williams, Rico Sennrich, Maria Nadejde, Matthias Huck, Eva Hasler, Philipp Koehn, In Proceedings of WMT 2014. [bib]

  • Dynamic Topic Adaptation for Phrase-based MT, Eva Hasler, Phil Blunsom, Philipp Koehn and Barry Haddow, In Proceedings of EACL 2014. [bib]

  • Sparse Lexicalised Features and Topic Adaptation for SMT, Eva Hasler, Barry Haddow and Philipp Koehn, In Proceedings of the International Workshop on Spoken Language Translation (IWSLT), Hong Kong, HK, December 2012. [bib]

  • The UEDIN Systems for the IWSLT 2012 Evaluation, Eva Hasler, Peter Bell, Arnab Ghoshal, Barry Haddow, Philipp Koehn, Fergus McInnes, Steve Renals and Pawel Swietojanski, In Proceedings of the International Workshop on Spoken Language Translation (IWSLT), Hong Kong, HK, December 2012.[slides][bib]

  • Hallucinated N-Best Lists for Discriminative Language Modeling, Kenji Sagae, Maider Lehr, Emily Prud'hommeaux, Puyang Xu, Nathan Glenn, Damianos Karakos, Sanjeev Khudanpur, Brian Roark, Murat Saraçlar, Izhak Shafran, Daniel Bikel, Chris Callison-Burch, Yuan Cao, Keith Hall, Eva Hasler, Philipp Koehn, Adam Lopez, Matt Post, Darcey Riley, IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2012.

  • Continuous Space Discriminative Language Modeling, Puyang Xu, Sanjeev Khudanpur, Maider Lehr, Emily Prud'hommeaux, Nathan Glenn, Damianos Karakos, Brian Roark, Kenji Sagae, Murat Saraçlar, Izhak Shafran, Dan Bikel, Chris Callison-Burch, Yuan Cao, Keith Hall, Eva Hasler, Philipp Koehn, Adam Lopez, Matt Post, Darcey Riley, IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2012.

  • Semi-Supervised Discriminative Language Modeling for Turkish ASR, Arda Çelebi, Haçim Sak, Erinç Dikici, Murat Saraçlar, Maider Lehr, Emily Tucker Prud'hommeaux, Puyang Xu, Nathan Glenn, Damianos Karakos, Sanjeev Khudanpur, Brian Roark, Kenji Sagae, Izhak Shafran, Dan Bikel, Chris Callison-Burch, Yuan Cao, Keith Hall, Eva Hasler, Philipp Koehn, Adam Lopez, Matt Post, Darcey Riley, IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2012.

  • Deriving conversation-based features from unlabeled speech for discriminative language modeling, Damianos Karakos, Brian Roark, Izhak Shafran, Kenji Sagae, Maider Lehr, Emily Prud'hommeaux, Puyang Xu, Nathan Glenn, Sanjeev Khudanpur, Murat Saraclar, Dan Bikel, Mark Dredze, Chris Callison-Burch, Yuan Cao, Keith Hall, Eva Hasler, Philip Koehn, Adam Lopez, Matt Post and Darcey Riley, InterSpeech, 2012.

  • Confusion-based Statistical Language Modeling for Machine Translation and Speech Recognition, Final report, JHU CLSP summer workshop project, 2011.

  • Margin Infused Relaxed Algorithm for Moses, Eva Hasler, Barry Haddow, Philipp Koehn, The Prague Bulletin of Mathematical Linguistics No. 96, 2011. [slides][bib]

  • Multi-engine machine translation with an open-source decoder for statistical machine translation, Yu Chen, Andreas Eisele, Christian Federmann, Eva Hasler, Michael Jellinghaus, & Silke Theison, In Proceedings of the Second Workshop on Statistical Machine Translation (WMT), 2007.

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