Informations and abstract
Keywords: Cross-Cultural Differences; Emotion Expression; Emotion Recognition; English; GRID; Language Corpora; Online Sorting; Polish; Pride; Social Robot; Translation.
The aim of the present study is to use the GRID, online emotions sorting, and corpus methodologies to illuminate different types of pride that an emotion-sensitive socially interacting robot would need to encode and decode in order to competently produce and recognise these and other types of emotions in different cultural social settings. The paper focuses on modelling different kinds of pride in contrastive cultural emotion models on the example of pride and duma in British English and Polish. As opposed to a focus on single emotions, we posit a viewpoint that centres on emotion clusters, which means that in the present study we focus not only on British English pride and its widely accepted Polish equivalent duma, but also on hubristic pride, which is represented in Polish by próżność and some of the senses of pycha as well as some other linked cluster members (contempt, conceit, slight, etc.). Divergent polarity marking in duma/pride items as well as some similarities in their basic metaphoricity are identified in terms of differing patterns of occurrence of particular GRID properties, emotion interconnectivity and clustering of translational equivalents in the two languages. We argue that, apart from the relevance of these findings for linguistics and psychology, such clustering should be at the heart of emotions modelling in social robots. In order to successfully use the emotion of pride in their interactions with humans, robots need to be sensitive to possible within-culture and cross-culture differences pertaining to such emotions, exemplified by British English and Polish in the present study, in addition to the core, deterministic attributes inferred for particular emotion concepts across cultures. Given the centrality of values to the emotion of pride, robots need to have the capacity to update from a knowledge base and learn from the situational context the set of values for each significant human that they interact with.