Bootstrapping Phrase-based Statistical Machine Translation via WSD Integration

Bootstrapping a Hybrid MT System to a New Language Pair

The usual concern when opting for a rule-based or a hybrid machine translation (MT) system is how much effort is required to adapt the system to a different language pair or a new domain. In this paper, we describe a way…

The AMU-UEDIN Submission to the WMT16 News Translation Task: Attention-based NMT Models as Feature Functions in Phrase-based SMT

This paper describes the AMU-UEDIN submissions to the WMT 2016 shared task on news translation. We explore methods of decode-time integration of attention-based neural translation models with phrase-based statistical mac…

HABLex: Human Annotated Bilingual Lexicons for Experiments in Machine Translation

Bilingual lexicons are valuable resources used by professional human translators. While these resources can be easily incorporated in statistical machine translation, it is unclear how to best do so in the neural framewo…

Interlocking Phrases in Phrase-based Statistical Machine Translation

Beyond Word-based Language Model in Statistical Machine Translation

Language model is one of the most important modules in statistical machine translation and currently the word-based language model dominants this community. However, many translation models (e.g. phrase-based models) gen…