About

Chiori Hori is a leading researcher at the intersection of robotics, artificial intelligence, and human-robot interaction, with a focus on enabling robots to understand and communicate with humans more naturally. Her work spans two critical frontiers: making robot speech sound less robotic and more conversational, and equipping robots with the ability to plan and replan tasks using large language models (LLMs). In her highly cited 2024 work on interactive planning for partially observable tasks, she demonstrates how LLMs can help robots handle open-vocabulary commands and adapt when things go wrong—a key step toward truly autonomous service robots. Earlier, she pioneered a cloud robotics approach to non-monologue speech synthesis, using Hidden Markov models to generate utterances that sound natural and friendly rather than monotonous, with her 2015 paper on dialogue-oriented robot speech earning 18 citations. Her recent 2025 paper on interactive robot action replanning using multimodal LLMs trained from human demonstration videos further advances the field, showing how robots can learn from video examples and adjust their actions in real time. With a career dedicated to making robots more capable conversational partners and autonomous agents, Hori’s work is essential reading for anyone interested in the future of intelligent, interactive robotics.

Research Focus

Key Achievements

4
H-Index
5
Papers
64
Total Citations
13
Avg Citations/Paper
🏆 Most Cited Paper
Interactive Planning Using Large Language Models for Partially Observable Robotic Tasks
23 citations · 2024
📈 Most Prolific Year: 2024 (1 Papers)
🤝 Key Collaborators: 18
🏛 Institutions: Mitsubishi Electric (United States), Kyoto Seika University, National Institute of Information and Communications Technology

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago