Generating politeness in task based interaction

Abstract

Politeness is an integral part of human language variation, e.g. consider the difference in the pragmatic effect of realizing the same communicative goal with either "Get me a glass of water mate!" or "I wonder if I could possibly have some water please?" This paper presents POLLy (Politeness for Language Learning), a system which combines a natural language generator with an AI Planner to model Brown and Levinson's theory of politeness (B&L) in collaborative task-oriented dialogue, with the ultimate goal of providing a fun and stimulating environment for learning English as a second language. An evaluation of politeness perceptions of POLLy's output shows that: (1) perceptions are generally consistent with B&L's predictions for choice of form and for discourse situation, i.e. utterances to strangers need to be much more polite than those to friends; (2) our indirect strategies which should be the politest forms, are seen as the rudest; and (3) English and Indian native speakers of English have different perceptions of the level of politeness needed to mitigate particular face threats.