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Main Authors: Miyoshi, Yuki, Inoue, Masaki, Fujimoto, Yusuke
Format: Preprint
Published: 2025
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Online Access:https://arxiv.org/abs/2511.11285
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author Miyoshi, Yuki
Inoue, Masaki
Fujimoto, Yusuke
author_facet Miyoshi, Yuki
Inoue, Masaki
Fujimoto, Yusuke
contents Natural language data, such as text and speech, have become readily available through social networking services and chat platforms. By leveraging human observations expressed in natural language, this paper addresses the problem of state estimation for physical systems, in which humans act as sensing agents. To this end, we propose a Language-Aided Particle Filter (LAPF), a particle filter framework that structures human observations via natural language processing and incorporates them into the update step of the state estimation. Finally, the LAPF is applied to the water level estimation problem in an irrigation canal and its effectiveness is demonstrated.
format Preprint
id arxiv_https___arxiv_org_abs_2511_11285
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Language-Aided State Estimation
Miyoshi, Yuki
Inoue, Masaki
Fujimoto, Yusuke
Systems and Control
Computation and Language
Natural language data, such as text and speech, have become readily available through social networking services and chat platforms. By leveraging human observations expressed in natural language, this paper addresses the problem of state estimation for physical systems, in which humans act as sensing agents. To this end, we propose a Language-Aided Particle Filter (LAPF), a particle filter framework that structures human observations via natural language processing and incorporates them into the update step of the state estimation. Finally, the LAPF is applied to the water level estimation problem in an irrigation canal and its effectiveness is demonstrated.
title Language-Aided State Estimation
topic Systems and Control
Computation and Language
url https://arxiv.org/abs/2511.11285