Abstract
We study the features crucial for a companion robot conceptual processing and suggest a practical implementation of a cognitive architecture that support these features while operating a real F-2 companion robot. The robot is designed to react to incoming speech and visual events, guide a person in a problem space and accumulate knowledge from texts and events in memory for further dialogue support. We show how a conceptual representation system designed for a companion robot deals with several types of conceptual representations: text semantics, sets of emotions and reactions, operations in a problem space and in semantic memory. We also suggest a conceptual representation based on linguistic valency structures (semantic predication) that is suitable to link the processing components. The general processing architecture is based on the production approach: it may trigger several scripts and combine speech and behavioral outputs of these scripts on the robot. The system performs conceptual operations with semantics while processing texts on a server in a standalone mode, or while controlling the robot in a dialogue mode, or assisting a user in solving Tangram puzzle.
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The present study has been supported by the Russian Science Foundation, project No 19-18-00547.
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Kotov, A., Zaidelman, L., Zinina, A., Arinkin, N., Filatov, A., Kivva, K. (2020). Conceptual Operations with Semantics for a Companion Robot. In: Karpov, A., Potapova, R. (eds) Speech and Computer. SPECOM 2020. Lecture Notes in Computer Science(), vol 12335. Springer, Cham. https://doi.org/10.1007/978-3-030-60276-5_24
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