Papers
5
Total Citations
64
H-Index
4
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
Top Papers
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- 2A cloud robotics approach towards dialogue-oriented robot speech18 citations · 2015
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