Humour as social dreaming:Stand-up comedy as therapeutic performance

Stand-up comedy binds dramatic cultural spectacle to ritualised, intimate exposure. Examining ‘case’ examples from live comic performance, this paper describes stand-up as a kind of social dreaming. The article proposes a theoretical frame drawing on Thomas Ogden’s notion of ‘talking as dreaming’ and psychoanalytic accounts connecting humour and melancholia. Locating the stand-up comedian’s propensity for humour in a specialist capacity to hone, display and process traumata, the paper characterises stand-up as a performative oscillation evoking paranoid-schizoid and depressive anxieties. A psychosocial gloss places stand-up as a cultural resource in the service of the popular-as-therapeutic. The paper articulates complementarities between Henri Bergson’s formulations on the function of laughter and an emergent object relations account in order to help to recognise ‘containing’ and ‘cultural-restorative’ aspects of much stand-up, understood as contemporary psychosocial ritual

Towards responsive Sensitive Artificial Listeners

This paper describes work in the recently started project SEMAINE, which aims to build a set of Sensitive Artificial Listeners – conversational agents designed to sustain an interaction with a human user despite limited verbal skills, through robust recognition and generation of non-verbal behaviour in real-time, both when the agent is speaking and listening. We report on data collection and on the design of a system architecture in view of real-time responsiveness

Reactive Statistical Mapping: Towards the Sketching of Performative Control with Data

Part 1: Fundamental IssuesInternational audienceThis paper presents the results of our participation to the ninth eNTERFACE workshop on multimodal user interfaces. Our target for this workshop was to bring some technologies currently used in speech recognition and synthesis to a new level, i.e. being the core of a new HMM-based mapping system. The idea of statistical mapping has been investigated, more precisely how to use Gaussian Mixture Models and Hidden Markov Models for realtime and reactive generation of new trajectories from inputted labels and for realtime regression in a continuous-to-continuous use case. As a result, we have developed several proofs of concept, including an incremental speech synthesiser, a software for exploring stylistic spaces for gait and facial motion in realtime, a reactive audiovisual laughter and a prototype demonstrating the realtime reconstruction of lower body gait motion strictly from upper body motion, with conservation of the stylistic properties. This project has been the opportunity to formalise HMM-based mapping, integrate various of these innovations into the Mage library and explore the development of a realtime gesture recognition tool

Laughter and Body Movements as Communicative Actions in Encounters

Peer reviewe

Motion Generation during Vocalized Emotional Expressions and Evaluation in Android Robots

Vocalized emotional expressions such as laughter and surprise often occur in natural dialogue interactions and are important factors to be considered in order to achieve smooth robot-mediated communication. Miscommunication may be caused if there is a mismatch between audio and visual modalities, especially in android robots, which have a highly humanlike appearance. In this chapter, motion generation methods are introduced for laughter and vocalized surprise events, based on analysis results of human behaviors during dialogue interactions. The effectiveness of controlling different modalities of the face, head, and upper body (eyebrow raising, eyelid widening/narrowing, lip corner/cheek raising, eye blinking, head motion, and torso motion control) and different motion control levels are evaluated using an android robot. Subjective experiments indicate the importance of each modality in the perception of motion naturalness (humanlikeness) and the degree of emotional expression