Handling uncertain input in multi-user human-robot interaction

Autor:	Oliver Lemon, Andre Gaschler, Manuel Giuliani, Mary Ellen Foster, Simon Keizer, Amy Isard
Rok vydání:	2014
Předmět:	Computer science business.industry Robot Artificial intelligence State (computer science) Multi-user business Baseline (configuration management) Action selection Human–robot interaction
Zdroj:	RO-MAN Keizer, S, Foster, M E, Gaschler, A, Giuliani, M, Isard, A & Lemon, O 2014, Handling uncertain input in multi-user human-robot interaction . in Proceedings of the 23rd IEEE International Symposium on Robot and Human Interactive Communication (IEEE RO-MAN 2014) . Institute of Electrical and Electronics Engineers (IEEE), pp. 312-317 . https://doi.org/10.1109/ROMAN.2014.6926271
ISSN:	1944-9445
DOI:	10.1109/roman.2014.6926271
Popis:	In this paper we present results from a user evaluation of a robot bartender system which handles state uncertainty derived from speech input by using belief tracking and generating appropriate clarification questions. We present a combination of state estimation and action selection components in which state uncertainty is tracked and exploited, and compare it to a baseline version that uses standard speech recognition confidence score thresholds instead of belief tracking. The results suggest that users are served fewer incorrect drinks when the uncertainty is retained in the state.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9c49ae0130c6d575756bbafcbe989f72 https://doi.org/10.1109/roman.2014.6926271 Zobrazit plný text záznamu