Social cognition, mindreading and narratives. A cognitive semiotics perspective on narrative practices from early mindreading to Autism Spectrum Disorder

Understanding social cognition referring to narratives without relying on mindreading skills has been the main aim of the Narrative Practice Hypothesis (NPH) proposed by Daniel Hutto and Shaun Gallagher. In this paper, I offer a semiotic reformulation of the NPH, expanding the notion of narrative beyond its conventional common-sense understanding and claiming that the kind of social cognition that operates in implicit false belief task competency is developed out of the narrative logic of interaction. I will try to show how experience is shaped through meaning by the structure of narrativity and the way this can account for how narrative competencies do not just depend on language acquisition, but permeate the interactive competencies of pre-linguistic children and some social non-human animals. Developing during primary and secondary intersubjectivity and rooted in the semiotic ability to deceive and manipulate others, semiotic narrativity is the key bridge that leads us to mind and beliefs starting from basic perceptions, emotions and embodied enactive interactions. I will test my Narrative Practice Semiotic Hypothesis (NPSH) on Autism spectrum disorders, where social cognition skills don’t work properly, connecting NPSH to the Social Motivation Theory of Autism (Dawson et al. 2005; Chevalier et al. 2012). I will finally answer some criticisms towards the original NPH, connecting its semiotic reformulation to early mindreading in infants and to some very recent experiments by Krupeneye et al. (2016) and Buttelmann et al. (2017) about false beliefs understanding in primates

M2D: Monolog to Dialog Generation for Conversational Story Telling

Storytelling serves many different social functions, e.g. stories are used to persuade, share troubles, establish shared values, learn social behaviors, and entertain. Moreover, stories are often told conversationally through dialog, and previous work suggests that information provided dialogically is more engaging than when provided in monolog. In this paper, we present algorithms for converting a deep representation of a story into a dialogic storytelling, that can vary aspects of the telling, including the personality of the storytellers. We conduct several experiments to test whether dialogic storytellings are more engaging, and whether automatically generated variants in linguistic form that correspond to personality differences can be recognized in an extended storytelling dialog