Learning and reusing dialog for repeated interactions with a situated social agent

• Content authoring for conversations is a limiting factor in creating verbal interactions with intelligent virtual agents. Building on techniques utilizing semi-situated learning in an incremental crowdworking pipeline, this paper introduces an embodied agent that self-authors its own dialog for social chat. In particular, the autonomous use of crowdworkers is supplemented with a generalization method that borrows and assesses the validity of dialog across conversational states. We argue that the approach offers a community-focused tailoring of dialog responses that is not available in approaches that rely solely on statistical methods across big data. We demonstrate the advantages that this can bring to interactions through data collected from 486 conversations between a situated social agent and 22 users during a 3 week long evaluation period.

Ämnesord

SAMHÄLLSVETENSKAP  -- Medie- och kommunikationsvetenskap -- Kommunikationsvetenskap (hsv//swe)

SOCIAL SCIENCES  -- Media and Communications -- Communication Studies (hsv//eng)

Nyckelord

Borrowing dialog

Repeated interactions

Social robot

Verbal chat

Publikations- och innehållstyp

ref (ämneskategori)

kon (ämneskategori)