We will conduct the following tutorial at IJCNLP2017 (2017/11/27-12/1) (8/10) †

• Fabien Cromieres, Toshiaki Nakazawa and Raj Dabre:
  Neural Machine Translation: Basics, Practical Aspects and Recent Trends

We will present following paper at PACLIC2017 (2017/11/16-18) (8/10) †

• Raj Dabre, Tetsuji Nakagawa and Hideto Kazawa:
  An Empirical Study of Language Relatedness for Transfer Learning in Neural Machine Translation (short; work done at Google)

We will present following paper at MT SUMMIT 2017 (2017/9/18-22) (8/10) †

• Raj Dabre, Fabien Cromieres, Toshiaki Nakazawa:
  Enabling Multi-Source Neural Machine Translation By Concatenating Source Sentences In Multiple Languages (long)

The following paper has been selected as Outstanding Paper of ACL2017 . (8/2) †

• Shuhei Kurita, Daisuke Kawahara and Sadao Kurohashi:
  Neural Joint Model for Transition-based Chinese Syntactic Analysis

John Richardson(Google) received 4th AAMT Nagao Student Award with his PhD thesis (2016/9) entitled "Improving Statistical Machine Translation with Target-Side Dependency Syntax." (6/14) †

Prof. Kurohashi and Prof. Kawahara received "The
Commendation for Science and Technology by the
Minister of Education, Culture, Sports, Science and
Technology" (Prizes for Science and Technology;
Research Category). (4/12) †

We will present following papers at ACL2017 (2017/7/30-8/4) (4/1) †

• Shuhei Kurita, Daisuke Kawahara and Sadao Kurohashi:
  Neural Joint Model for Transition-based Chinese Syntactic Analysis

• Chenhui Chu, Raj Dabre and Sadao Kurohashi:
  An Empirical Comparison of Domain Adaptation Methods for Neural Machine Translation (short)

• Gongye Jin, Daisuke Kawahara and Sadao Kurohashi:
  Improving Chinese Semantic Role Labeling using High-quality Surface and Deep Case Frames

Search Engine Infrastructure based on Deep Natural Language Processing †

The essential purpose of information retrieval is not to retrieve just a relevant document but to acquire the information or knowledge in the document. We have been developing a next-generation infrastructure of information retrieval on the basis of the following techniques of deep natural language processing: precise processing based not on words but on predicate-argument structures, identifying the variety of linguistic expressions and providing a bird's-eye view of search results via clustering and interaction.

Machine Translation †

To bring automatic translation by computers to the level of human translation, we have been studying next-generation methodology of machine translation on the basis of text understanding and a large collection of translation examples. We have already accomplished practical translation on the domain of travel conversation, and constructed a translation-aid system that can be used by experts of patent translation.