We will present the following papers at AACL-IJCNLP2022 (2022/11/20-23) †

• Haiyue Song, Raj Dabre, Zhuoyuan Mao, Chenhui Chu, Sadao Kurohashi:
  BERTSeg: BERT Based Unsupervised Subword Segmentation for Neural Machine Translation

• Yibin Shen, Qianying Liu, Zhuoyuan Mao, Zhen Wan, Fei Cheng and Sadao Kurohashi:
  Seeking Diverse Reasoning Logic: Controlled Equation Expression Generation for Solving Math Word Problems

• Jumon Nozaki and Yugo Murawaki:
  Addressing Segmentation Ambiguity in Neural Linguistic Steganography

Project Researcher Taro Okahisa moved to Shizuoka University as an Assistant Professor. (2021/7/1) †

We will present the following paper at CRAC2022 (2022/10) †

• Nobuhiro Ueda and Sadao Kurohashi:
  Improving Bridging Reference Resolution using Continuous Essentiality from Crowdsourcing

We will present the following paper at COLING2022 (2022/10/12-17) †

• Kazumasa Omura and Sadao Kurohashi:
  Improving Commonsense Contingent Reasoning by Pseudo-data and its Application to the Related Tasks

The following paper received the Ourstanding Research Award of the 253-th Special Interest Group of Natural Language Processing (2022/9) †

• Nobuhiro Ueda, Kazumasa Omura, Takashi Kodama, Hirokazu Kiyomaru, Yugo Murawaki, Daisuke Kawahara and Sadao Kurohashi:
  KWJA: A Japanese Analyzer Based on Pre-trained Language Models

We will present the following papers at Interspeech 2022 (2022/9) †

• Zhengdong Yang, Wangjin Zhou, Chenhui Chu, Sheng Li, Raj Dabre, Raphael Rubino and Yi Zhao:
  Fusion of Self-supervised Learned Models for MOS Prediction

• Kak Soky, Sheng Li, Masato Mimura, Chenhui Chu and Tatsuya Kawahara:
  Leveraging Simultaneous Translation for Enhancing Transcription of Low-resource Language via Cross Attention Mechanism

Associate Professor Chu received a Google Research Scholar Award for his Visual Scene-Aware Machine Translation research proposal. (2022/4) †

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.