Semantic comprehension system for f-2 emotional robot

Abstract

Within the project of F-2 personal robot we design a system for automatic text comprehension (parser). It enables the robot to choose “relevant” emotional reactions (output speech and gestures) to an incoming text – currently in Russian. The system executes morphological and syntactic analysis of the text and further constructs its semantic representation. This is a shallow representation where a set of semantic markers (lexical semantics) is distributed between a set of semantic roles – structure of the situation (fact). This representation may be used as (a) fact description – to search for facts with a given structure and (b) basis to invoke emotional reactions (gestures, facial expressions and utterances) to be performed by the personal robot within a dialogue. We argue that the execution of a relevant emotional reaction can be considered as a characteristic of text comprehension by computer systems.