Emerging Linguistic Functions in Early Infancy

This paper presents results from experimental studies on early language acquisition in infants and attempts to interpret the experimental results within the framework of the Ecological Theory of Language Acquisition (ETLA) recently proposed by (Lacerda et al., 2004a). From this perspective, the infant’s first steps in the acquisition of the ambient language are seen as a consequence of the infant’s general capacity to represent sensory input and the infant’s interaction with other actors in its immediate ecological environment. On the basis of available experimental evidence, it will be argued that ETLA offers a productive alternative to traditional descriptive views of the language acquisition process by presenting an operative model of how early linguistic function may emerge through interaction

The perception of emotion in artificial agents

Given recent technological developments in robotics, artificial intelligence and virtual reality, it is perhaps unsurprising that the arrival of emotionally expressive and reactive artificial agents is imminent. However, if such agents are to become integrated into our social milieu, it is imperative to establish an understanding of whether and how humans perceive emotion in artificial agents. In this review, we incorporate recent findings from social robotics, virtual reality, psychology, and neuroscience to examine how people recognize and respond to emotions displayed by artificial agents. First, we review how people perceive emotions expressed by an artificial agent, such as facial and bodily expressions and vocal tone. Second, we evaluate the similarities and differences in the consequences of perceived emotions in artificial compared to human agents. Besides accurately recognizing the emotional state of an artificial agent, it is critical to understand how humans respond to those emotions. Does interacting with an angry robot induce the same responses in people as interacting with an angry person? Similarly, does watching a robot rejoice when it wins a game elicit similar feelings of elation in the human observer? Here we provide an overview of the current state of emotion expression and perception in social robotics, as well as a clear articulation of the challenges and guiding principles to be addressed as we move ever closer to truly emotional artificial agents

Integration of Action and Language Knowledge: A Roadmap for Developmental Robotics

“This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder." “Copyright IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.”This position paper proposes that the study of embodied cognitive agents, such as humanoid robots, can advance our understanding of the cognitive development of complex sensorimotor, linguistic, and social learning skills. This in turn will benefit the design of cognitive robots capable of learning to handle and manipulate objects and tools autonomously, to cooperate and communicate with other robots and humans, and to adapt their abilities to changing internal, environmental, and social conditions. Four key areas of research challenges are discussed, specifically for the issues related to the understanding of: 1) how agents learn and represent compositional actions; 2) how agents learn and represent compositional lexica; 3) the dynamics of social interaction and learning; and 4) how compositional action and language representations are integrated to bootstrap the cognitive system. The review of specific issues and progress in these areas is then translated into a practical roadmap based on a series of milestones. These milestones provide a possible set of cognitive robotics goals and test scenarios, thus acting as a research roadmap for future work on cognitive developmental robotics.Peer reviewe

Creating the cognitive form of phonological units: The speech sound correspondence problem in infancy could be solved by mirrored vocal interactions rather than by imitation

Theories about the cognitive nature of phonological units have been constrained by the assumption that young children solve the correspondence problem for speech sounds by imitation, whether by an auditory- or gesture-based matching to target process. Imitation on the part of the child implies that he makes a comparison within one of these domains, which is presumed to be the modality of the underlying representation of speech sounds. However, there is no evidence that the correspondence problem is solved in this way. Instead we argue that the child can solve it through the mirroring behaviour of his caregivers within imitative interactions and that this mechanism is more consistent with the developmental data. The underlying representation formed by mirroring is intrinsically perceptuo-motor. It is created by the association of a vocal action performed by the child and the reformulation of this into an L1 speech token that he hears in return. Our account of how production and perception develop incorporating this mechanism explains some longstanding problems in speech and reconciles data from psychology and neuroscience

Predicting continuous conflict perception with Bayesian Gaussian processes

Conflict is one of the most important phenomena of social life, but it is still largely neglected by the computing community. This work proposes an approach that detects common conversational social signals (loudness, overlapping speech, etc.) and predicts the conflict level perceived by human observers in continuous, non-categorical terms. The proposed regression approach is fully Bayesian and it adopts Automatic Relevance Determination to identify the social signals that influence most the outcome of the prediction. The experiments are performed over the SSPNet Conflict Corpus, a publicly available collection of 1430 clips extracted from televised political debates (roughly 12 hours of material for 138 subjects in total). The results show that it is possible to achieve a correlation close to 0.8 between actual and predicted conflict perception

Developing Self-Awareness in Robots via Inner Speech

The experience of inner speech is a common one. Such a dialogue accompanies the introspection of mental life and fulfills essential roles in human behavior, such as self-restructuring, self-regulation, and re-focusing on attentional resources. Although the underpinning of inner speech is mostly investigated in psychological and philosophical fields, the research in robotics generally does not address such a form of self-aware behavior. Existing models of inner speech inspire computational tools to provide a robot with this form of self-awareness. Here, the widespread psychological models of inner speech are reviewed, and a cognitive architecture for a robot implementing such a capability is outlined in a simplified setup

Cerebellar mutism syndrome: from pathophysiology to rehabilitation

Cerebellar mutism syndrome (CMS) is a common complication following surgical resection of childhood tumors arising in the posterior fossa. Alteration of linguistic production, up to muteness and emotional lability, generally reported at least 24 h after the intervention, is the hallmark of post-operative CMS. Other associated traits include hypotonia and other cerebellar motor signs, cerebellar cognitive-affective syndrome, motor deficits from the involvement of the long pathways, and cranial neuropathies. Recovery usually takes 6 months, but most children are burdened with long-term residual deficits. The pathogenic mechanism is likely due to the damage occurring to the proximal efferent cerebellar pathway, including the dentate nucleus, the superior cerebellar peduncle, and its decussation in the mesencephalic tegmentum. Proven risk factors include brain stem invasion, diagnosis of medulloblastoma, midline localization, tumor size, invasion of the fourth ventricle, invasion of the superior cerebellar peduncle, left-handedness, and incision of the vermis. Currently, rehabilitation is the cornerstone of the treatment of patients with cerebellar mutism syndrome, and it must consider the three main impaired domains, namely speech, cognition/behavior, and movement

Spoken language processing: piecing together the puzzle

Attempting to understand the fundamental mechanisms underlying spoken language processing, whether it is viewed as behaviour exhibited by human beings or as a faculty simulated by machines, is one of the greatest scientific challenges of our age. Despite tremendous achievements over the past 50 or so years, there is still a long way to go before we reach a comprehensive explanation of human spoken language behaviour and can create a technology with performance approaching or exceeding that of a human being. It is argued that progress is hampered by the fragmentation of the field across many different disciplines, coupled with a failure to create an integrated view of the fundamental mechanisms that underpin one organism's ability to communicate with another. This paper weaves together accounts from a wide variety of different disciplines concerned with the behaviour of living systems - many of them outside the normal realms of spoken language - and compiles them into a new model: PRESENCE (PREdictive SENsorimotor Control and Emulation). It is hoped that the results of this research will provide a sufficient glimpse into the future to give breath to a new generation of research into spoken language processing by mind or machine. (c) 2007 Elsevier B.V. All rights reserved