What's New

We will hold a briefing session (2023/5/13)

As part of the admission orientation of the Intelligence Science and Technology Course held on 13 May, 2023, our lab will have a briefing session. Please register on the course website.

The following papers received the excellence award of the 29-th annual meeting of the association for natural language processing (2023/3)

  • Tatsuro Inaba, Hirokazu Kiyomaru, Fei Cheng, Sadao Kurohashi:
    A Reasoning Framework Using Multiple External Tools based on Large Language Models

The following papers received the young researcher award of the 29-th annual meeting of the association for natural language processing (2023/3)

  • Koki Watanabe, Yugo Murawaki, Sadao Kurohashi:
    Extracting Textual Expressions Characteristic of a Population by Means of Interpreting Neural Classifier Predictions: A Case Study in Americans
  • Shunya Kato, Shuhei Kurita, Chenhui Chu, Sadao Kurohashi:
    ARKitSceneRefer: Text-based Localization of Small Objects in Diverse Real-World 3D Indoor Scenes
  • Shiho Matta, Yin Jou Huang, Hirokazu Kiyomaru, Sadao Kurohashi:
    Utilizing Pseudo Dialogue in Conversational Semantic Frame Analysis

The following papers received the special committee award of the 29-th annual meeting of the association for natural language processing (2023/3)

  • Nobuhiro Ueda, Hideko Habe, Akishige Yuguchi, Seiya Kawano, Yasumoto Kawanishi, Sadao Kurohashi, Koichiro Yoshino:
    Construction of a Multi-modal Dialogue Dataset for Comprehensive Real-world Reference Resolution

We will present the following papers at ICASSP2023 (2023/6)

  • Qianying Liu, Zhuo Gong, Zhengdong Yang, Yuhang Yang, Sheng Li, Chenchen Ding, Nobuaki Minematsu, Hao Huang, Fei Cheng, Chenhui Chu, Sadao Kurohashi:
    Hierarchical Softmax for End-to-End Low-resource Multilingual Speech Recognition
  • Kak Soky, Sheng Li, Chenhui Chu, Tatsuya Kawahara:
    Domain and Language Adaptation Using Heterogeneous Datasets for Wav2vec2.0-based Speech Recognition of Low-resource Language

Post-doctoral researcher Huang Yin Jou starts working at the Graduate School of Informatics, Kyoto University as a program-specific assistant professor.

We will present the following papers at EACL2023 (2023/5).

  • Zhuoyuan Mao and Tetsuji Nakagawa:
    LEALLA: Learning Lightweight Language-agnostic Sentence Embedding with Knowledge Distillation
  • Qianying Liu, Wenyu Guan, Jianhao Shen, Fei Cheng and Sadao Kurohashi:
    ComSearch:Equation Searching with Combinatorial Strategy for Solving Math Word Problems with Weak Supervision
  • Zhen Wan, Fei Cheng, Qianying Liu, Zhuoyuan Mao, Haiyue Song and Sadao Kurohashi:
    Relation Extraction with Weighted Contrastive Pre-training on Distant Supervision (Findings)

Research Overview

Language is the most reliable medium of human intellectual activities. Our objective is to establish the technology and academic discipline for handling and understanding language, in a manner that is as close as possible to that of humans, using computers. These include syntactic language analysis, semantic analysis, context analysis, text comprehension, text generation and dictionary systems to develop various application systems for machine translation and information retrieval.

Search Engine Infrastructure based on Deep Natural Language Processing

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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

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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.

Fundamental Studies on Text Understanding

To make computers understand language, it is essential to give computers world knowledge. This was a very hard problem ten years ago, but it has become possible to acquire knowledge from a massive amount of text in virtue of the drastic progress of computing power and network. We have successfully acquired linguistic patterns of predicate-argument structures from automatic parses of 7 billion Japanese sentences crawled from the Web using grid computing machines. By utilizing such knowledge, we study text understanding, i.e., recognizing the relationships between words and phrases in text.

Policy Regarding Acceptance of Students from Outside

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