Co-constructing intersubjectivity with artificial conversational agents: people are more likely to initiate repairs of misunderstandings with agents represented as human

This article explores whether people more frequently attempt to repair misunderstandings when speaking to an artificial conversational agent if it is represented as fully human. Interactants in dyadic conversations with an agent (the chat bot Cleverbot) spoke to either a text screen interface (agent's responses shown on a screen) or a human body interface (agent's responses vocalized by a human speech shadower via the echoborg method) and were either informed or not informed prior to interlocution that their interlocutor's responses would be agent-generated. Results show that an interactant is less likely to initiate repairs when an agent-interlocutor communicates via a text screen interface as well as when they explicitly know their interlocutor's words to be agent-generated. That is to say, people demonstrate the most “intersubjective effort” toward establishing common ground when they engage an agent under the same social psychological conditions as face-to-face human-human interaction (i.e., when they both encounter another human body and assume that they are speaking to an autonomously-communicating person). This article's methodology presents a novel means of benchmarking intersubjectivity and intersubjective effort in human-agent interaction

An integrated theory of language production and comprehension

Currently, production and comprehension are regarded as quite distinct in accounts of language processing. In rejecting this dichotomy, we instead assert that producing and understanding are interwoven, and that this interweaving is what enables people to predict themselves and each other. We start by noting that production and comprehension are forms of action and action perception. We then consider the evidence for interweaving in action, action perception, and joint action, and explain such evidence in terms of prediction. Specifically, we assume that actors construct forward models of their actions before they execute those actions, and that perceivers of others' actions covertly imitate those actions, then construct forward models of those actions. We use these accounts of action, action perception, and joint action to develop accounts of production, comprehension, and interactive language. Importantly, they incorporate well-defined levels of linguistic representation (such as semantics, syntax, and phonology). We show (a) how speakers and comprehenders use covert imitation and forward modeling to make predictions at these levels of representation, (b) how they interweave production and comprehension processes, and (c) how they use these predictions to monitor the upcoming utterances. We show how these accounts explain a range of behavioral and neuroscientific data on language processing and discuss some of the implications of our proposal

Spectators’ aesthetic experiences of sound and movement in dance performance

In this paper we present a study of spectators’ aesthetic experiences of sound and movement in live dance performance. A multidisciplinary team comprising a choreographer, neuroscientists and qualitative researchers investigated the effects of different sound scores on dance spectators. What would be the impact of auditory stimulation on kinesthetic experience and/or aesthetic appreciation of the dance? What would be the effect of removing music altogether, so that spectators watched dance while hearing only the performers’ breathing and footfalls? We investigated audience experience through qualitative research, using post-performance focus groups, while a separately conducted functional brain imaging (fMRI) study measured the synchrony in brain activity across spectators when they watched dance with sound or breathing only. When audiences watched dance accompanied by music the fMRI data revealed evidence of greater intersubject synchronisation in a brain region consistent with complex auditory processing. The audience research found that some spectators derived pleasure from finding convergences between two complex stimuli (dance and music). The removal of music and the resulting audibility of the performers’ breathing had a significant impact on spectators’ aesthetic experience. The fMRI analysis showed increased synchronisation among observers, suggesting greater influence of the body when interpreting the dance stimuli. The audience research found evidence of similar corporeally focused experience. The paper discusses possible connections between the findings of our different approaches, and considers the implications of this study for interdisciplinary research collaborations between arts and sciences

Towards a complete multiple-mechanism account of predictive language processing [Commentary on Pickering & Garrod]

Although we agree with Pickering & Garrod (P&G) that prediction-by-simulation and prediction-by-association are important mechanisms of anticipatory language processing, this commentary suggests that they: (1) overlook other potential mechanisms that might underlie prediction in language processing, (2) overestimate the importance of prediction-by-association in early childhood, and (3) underestimate the complexity and significance of several factors that might mediate prediction during language processing

Social Learning Systems: The Design of Evolutionary, Highly Scalable, Socially Curated Knowledge Systems

In recent times, great strides have been made towards the advancement of automated reasoning and knowledge management applications, along with their associated methodologies. The introduction of the World Wide Web peaked academicians’ interest in harnessing the power of linked, online documents for the purpose of developing machine learning corpora, providing dynamical knowledge bases for question answering systems, fueling automated entity extraction applications, and performing graph analytic evaluations, such as uncovering the inherent structural semantics of linked pages. Even more recently, substantial attention in the wider computer science and information systems disciplines has been focused on the evolving study of social computing phenomena, primarily those associated with the use, development, and analysis of online social networks (OSN\u27s). This work followed an independent effort to develop an evolutionary knowledge management system, and outlines a model for integrating the wisdom of the crowd into the process of collecting, analyzing, and curating data for dynamical knowledge systems. Throughout, we examine how relational data modeling, automated reasoning, crowdsourcing, and social curation techniques have been exploited to extend the utility of web-based, transactional knowledge management systems, creating a new breed of knowledge-based system in the process: the Social Learning System (SLS). The key questions this work has explored by way of elucidating the SLS model include considerations for 1) how it is possible to unify Web and OSN mining techniques to conform to a versatile, structured, and computationally-efficient ontological framework, and 2) how large-scale knowledge projects may incorporate tiered collaborative editing systems in an effort to elicit knowledge contributions and curation activities from a diverse, participatory audience

Cognitive Grammar in Literature

This is the first book to present an account of literary meaning and effects drawing on our best understanding of mind and language in the form of a Cognitive Grammar. The contributors provide exemplary analyses of a range of literature from science fiction, dystopia, absurdism and graphic novels to the poetry of Wordsworth, Hopkins, Sassoon, Balassi, and Dylan Thomas, as well as Shakespeare, Chaucer, Barrett Browning, Whitman, Owen and others. The application of Cognitive Grammar allows the discussion of meaning, translation, ambience, action, reflection, multimodality, empathy, experience and literariness itself to be conducted in newly valid ways. With a Foreword by the creator of Cognitive Grammar, Ronald Langacker, and an Afterword by the cognitive scientist Todd Oakley, the book represents the latest advance in literary linguistics, cognitive poetics and literary critical practice