We will present the following papers at Interspeech 2025 (2025/8). †

• Zaid Sheikh, Shuichiro Shimizu, Siddhant Arora, Jiatong Shi, Samuele Cornell, Xinjian Li, Shinji Watanabe:
  Scalable Spontaneous Speech Dataset (SSSD): Crowdsourcing Data Collection to Promote Dialogue Research.
• Brian Yan, Injy Hamed, Shuichiro Shimizu, Vasista Lodagala, William Chen, Olga Iakovenko, Bashar Talafha, Amir Hussein, Alexander Polok, Kalvin Chang, Dominik Klement, Sara Althubaiti, Puyuan Peng, Matthew Wiesner, Thamar Solorio, Ahmed Ali, Sanjeev Khudanpur, Shinji Watanabe, Chih-Chen Chen, Zhen Wu, Karim Benharrak, Anuj Diwan, Samuele Cornell, Eunjung Yeo, Kwanghee Choi, Carlos Carvalho, Karen Rosero:
  CS-FLEURS: A Massively Multilingual and Code-Switched Speech Dataset.

We will present the following papers at ACL 2025 (2025/7-8). †

• Zhen Wan, Chao-Han Huck Yang, Yahan Yu, Jinchuan Tian, Sheng Li, Ke Hu, Zhehuai Chen, Shinji Watanabe, Fei Cheng, Chenhui Chu, Sadao Kurohashi:
  SIQ: Exterminating Speech Intelligence Quotient Cross Cognitive Levels in Voice Understanding Large Language Models
• Zhengdong Yang, Sheng Li, Chenhui Chu:
  Generative Error Correction for Emotion-aware Speech-to-text Translation (Findings)
• Zhengdong Yang, Shuichiro Shimizu, Yahan Yu, Chenhui Chu:
  When Large Language Models Meet Speech: A Survey on Integration Approaches (Findings)
• Chengzhi Zhong, Qianying Liu, Fei Cheng, Junfeng Jiang, Zhen Wan, Chenhui Chu, Yugo Murawaki, Sadao Kurohashi:
  What Language Do Non-English-Centric Large Language Models Think in? (Findings)
• Yahan Yu, Duzhen Zhang, Yong Ren, Xuanle Zhao, Xiuyi Chen, Chenhui Chu:
  Progressive LoRA for Multimodal Continual Instruction Tuning (Findings)
• Qianying Liu, Katrina Qiyao Wang, Fei Cheng, Sadao Kurohashi:
  7 Points to Tsinghua but 10 Points to 清华? Assessing Large Language Models in Agentic Multilingual National Bias (Findings)
• Yen-Ting Lin, Zhehuai Chen, Piotr Zelasko, Zhen Wan, Xuesong Yang, Zih-Ching Chen, Krishna C Puvvada, Ke Hu, Szu-Wei Fu, Jun Wei Chiu, Jagadeesh Balam, Boris Ginsburg, Yu-Chiang Frank Wang, Chao-Han Huck Yang:
  NeKo: Cross-Modality Post-Recognition Error Correction with Tasks-Guided Mixture-of-Experts Language Model (Industry)

The following work received the Best Presentaiton Award at the 13th AAMT for young Translation Research Group †

• Chengzhi Zhong, Fei Cheng, Qianying Liu, Junfeng Jiang, Zhen Wan, Chenhui Chu, Yugo Murawaki, Sadao Kurohashi:
  What language do Japanese-specialized large language models think in?

We will hold a briefing session (2025/5/10) †

• As part of the admission orientation of the Intelligence Science and Technology Course held on 10 May, 2025, our lab will have an onsite briefing session after the course-wide session. We plan to hold two briefing sessions from 15:00 and 16:00, respectively.

We will present the following paper at NAACL 2025 (2025/4-5) . †

• Siddhant Arora, Yifan Peng, Jiatong Shi, Jinchuan Tian, William Chen, Shikhar Bharadwaj, Hayato Futami, Yosuke Kashiwagi, Emiru Tsunoo, Shuichiro Shimizu, Vaibhav Srivastav, Shinji Watanabe:
  ESPnet-SDS: Unified Toolkit and Demo for Spoken Dialogue Systems (System Demonstrations)
• Shiho Matta, Yin Jou Huang, Fei Cheng, Hirokazu Kiyomaru, Yugo Murawaki:
  Optimizing Cost-Efficiency with LLM-Generated Training Data for Conversational Semantic Frame Analysis (Joint SIGHUM Workshop, LaTeCH-CLfL2025)

Dr. Jivnesh Sandhan joined our lab as a researcher. (2024/12/1) †

We climbed Mount Daimonji. (11/27) †

We will present the following papers at EMNLP 2024(2024/11) †

• Yin Jou Huang, Rafik Hadfi: How Personality Traits Influence Negotiation Outcomes? A Simulation based on Large Language Models (Findings)
• Junfeng Jiang, Fei Cheng, Akiko Aizawa: Improving Referring Ability for Biomedical Language Models (Findings)

Zhuoyuan Mao who got his Ph.D. degree last fiscal year received the AAMT Nagao Award Student Encouragement Award for his following doctoral thesis (2024/5). †

• Breaking Language Barriers: Enhancing Multilingual Representation for Sentence Alignment and Translation

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.