We describe a novel approach to machine translation that combines the strengths of the two leading corpus-based approaches: Phrasal SMT and EBMT. We use a syntactically informed d...
We reveal a previously unnoticed connection between dependency parsing and statistical machine translation (SMT), by formulating the dependency parsing task as a problem of word a...
In this paper we investigate the automatic generation and evaluation of sentential paraphrases. We describe a method for generating sentential paraphrases by using a large aligned...
Automatic speech recognition (ASR) results contain not only ASR errors, but also disfluencies and colloquial expressions that must be corrected to create readable transcripts. We...
Graham Neubig, Yuya Akita, Shinsuke Mori, Tatsuya ...
In our research, we have developed a transfer-based machine translation architecture for the translation from Japanese into German. One main feature of the system is the fully auto...