12,765 research outputs found

    Affective Medicine: a review of Affective Computing efforts in Medical Informatics

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    Background: Affective computing (AC) is concerned with emotional interactions performed with and through computers. It is defined as “computing that relates to, arises from, or deliberately influences emotions”. AC enables investigation and understanding of the relation between human emotions and health as well as application of assistive and useful technologies in the medical domain. Objectives: 1) To review the general state of the art in AC and its applications in medicine, and 2) to establish synergies between the research communities of AC and medical informatics. Methods: Aspects related to the human affective state as a determinant of the human health are discussed, coupled with an illustration of significant AC research and related literature output. Moreover, affective communication channels are described and their range of application fields is explored through illustrative examples. Results: The presented conferences, European research projects and research publications illustrate the recent increase of interest in the AC area by the medical community. Tele-home healthcare, AmI, ubiquitous monitoring, e-learning and virtual communities with emotionally expressive characters for elderly or impaired people are few areas where the potential of AC has been realized and applications have emerged. Conclusions: A number of gaps can potentially be overcome through the synergy of AC and medical informatics. The application of AC technologies parallels the advancement of the existing state of the art and the introduction of new methods. The amount of work and projects reviewed in this paper witness an ambitious and optimistic synergetic future of the affective medicine field

    Children\u27s Sensitivity to Pitch Variation in Language

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    Children acquire consonant and vowel categories by 12 months, but take much longer to learn to interpret perceptible variation. This dissertation considers children’s interpretation of pitch variation. Pitch operates, often simultaneously, at different levels of linguistic structure. English-learning children must disregard pitch at the lexical level—since English is not a tone language—while still attending to pitch for its other functions. Chapters 1 and 5 outline the learning problem and suggest ways children might solve it. Chapter 2 demonstrates that 2.5-year-olds know pitch cannot differentiate words in English. Chapter 3 finds that not until age 4–5 do children correctly interpret pitch cues to emotions. Chapter 4 demonstrates some sensitivity between 2.5 and 5 years to the pitch cue to lexical stress, but continuing difficulties at the older ages. These findings suggest a late trajectory for interpretation of prosodic variation; throughout, I propose explanations for this protracted time-course

    Continuous Analysis of Affect from Voice and Face

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    Human affective behavior is multimodal, continuous and complex. Despite major advances within the affective computing research field, modeling, analyzing, interpreting and responding to human affective behavior still remains a challenge for automated systems as affect and emotions are complex constructs, with fuzzy boundaries and with substantial individual differences in expression and experience [7]. Therefore, affective and behavioral computing researchers have recently invested increased effort in exploring how to best model, analyze and interpret the subtlety, complexity and continuity (represented along a continuum e.g., from −1 to +1) of affective behavior in terms of latent dimensions (e.g., arousal, power and valence) and appraisals, rather than in terms of a small number of discrete emotion categories (e.g., happiness and sadness). This chapter aims to (i) give a brief overview of the existing efforts and the major accomplishments in modeling and analysis of emotional expressions in dimensional and continuous space while focusing on open issues and new challenges in the field, and (ii) introduce a representative approach for multimodal continuous analysis of affect from voice and face, and provide experimental results using the audiovisual Sensitive Artificial Listener (SAL) Database of natural interactions. The chapter concludes by posing a number of questions that highlight the significant issues in the field, and by extracting potential answers to these questions from the relevant literature. The chapter is organized as follows. Section 10.2 describes theories of emotion, Sect. 10.3 provides details on the affect dimensions employed in the literature as well as how emotions are perceived from visual, audio and physiological modalities. Section 10.4 summarizes how current technology has been developed, in terms of data acquisition and annotation, and automatic analysis of affect in continuous space by bringing forth a number of issues that need to be taken into account when applying a dimensional approach to emotion recognition, namely, determining the duration of emotions for automatic analysis, modeling the intensity of emotions, determining the baseline, dealing with high inter-subject expression variation, defining optimal strategies for fusion of multiple cues and modalities, and identifying appropriate machine learning techniques and evaluation measures. Section 10.5 presents our representative system that fuses vocal and facial expression cues for dimensional and continuous prediction of emotions in valence and arousal space by employing the bidirectional Long Short-Term Memory neural networks (BLSTM-NN), and introduces an output-associative fusion framework that incorporates correlations between the emotion dimensions to further improve continuous affect prediction. Section 10.6 concludes the chapter

    A Study of Non-Linguistic Utterances for Social Human-Robot Interaction

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    The world of animation has painted an inspiring image of what the robots of the future could be. Taking the robots R2D2 and C3PO from the Star Wars films as representative examples, these robots are portrayed as being more than just machines, rather, they are presented as intelligent and capable social peers, exhibiting many of the traits that people have also. These robots have the ability to interact with people, understand us, and even relate to us in very personal ways through a wide repertoire of social cues. As robotic technologies continue to make their way into society at large, there is a growing trend toward making social robots. The field of Human-Robot Interaction concerns itself with studying, developing and realising these socially capable machines, equipping them with a very rich variety of capabilities that allow them to interact with people in natural and intuitive ways, ranging from the use of natural language, body language and facial gestures, to more unique ways such as expression through colours and abstract sounds. This thesis studies the use of abstract, expressive sounds, like those used iconically by the robot R2D2. These are termed Non-Linguistic Utterances (NLUs) and are a means of communication which has a rich history in film and animation. However, very little is understood about how such expressive sounds may be utilised by social robots, and how people respond to these. This work presents a series of experiments aimed at understanding how NLUs can be utilised by a social robot in order to convey affective meaning to people both young and old, and what factors impact on the production and perception of NLUs. Firstly, it is shown that not all robots should use NLUs. The morphology of the robot matters. People perceive NLUs differently across different robots, and not always in a desired manner. Next it is shown that people readily project affective meaning onto NLUs though not in a coherent manner. Furthermore, people's affective inferences are not subtle, rather they are drawn to well established, basic affect prototypes. Moreover, it is shown that the valence of the situation in which an NLU is made, overrides the initial valence of the NLU itself: situational context biases how people perceive utterances made by a robot, and through this, coherence between people in their affective inferences is found to increase. Finally, it is uncovered that NLUs are best not used as a replacement to natural language (as they are by R2D2), rather, people show a preference for them being used alongside natural language where they can play a supportive role by providing essential social cues

    Emotion and imitation in early infant-parent interaction: a longitudinal and cross-cultural study

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    Following a brief introduction to the diverse views on the motives for imitation, a review of the literature is presented covering the following topics: early theories and observations concerning the origin and development of human imitation in infancy; recent theoretical models that have emerged from experimental studies of infant imitation and from naturalistic studies of imitation in infant -mother communication; and traditional and recent theoretical and empirical approaches to imitative phenomena in infant -father interaction. This review leads to the following conclusions:a) The failure of attempts to confirm certain ideas, hypotheses and suggestions built into the theories and strategies of earlier studies does not detract from their great contribution, which set the foundations upon which recent research is carried forward.b) Despite the different theoretical frameworks and the lack of a consensus as to the best method for investigating early imitative phenomena in experimental settings, neonatal imitation is now accepted as a fact.c) Imitative phenomena found in empirical studies focusing on infant -father interaction, as well as the relevant theoretical interpretations, are characterised by a contradiction; theory predicts bidirectional regulations, but studies employ an empirical approach that favours the view that regulation is only on the parental side.In this investigation, observations were made of thirty infants, fifteen from Greece and fifteen from Scotland. All were seen every 15 days interacting with their mothers and with their fathers at home, from the 8th to the 24th week of life. A total of 540 home recordings were made. Units of interaction that contained imitative episodes were subjected to microanalysis with the aid of specialized software, in a multi -media system that provides the capability for detection, recording, timing and signal analysis of the variables under consideration to an accuracy of 1 /25th of a second.The main findings may be summarised as follows: a) Imitation was evident, as early as the 8th week, irrespective of the country, the parent or the infant's sex. b) Cultural differences, reflecting the predominance of non -vocal and vocal imitative expressive behaviour in the two countries, were found. c) The developmental course of early imitative expressive behaviours was typically non -linear. d) Turn-taking imitative exchanges predominated over co-actions. e) Parents were found to imitate their infants more than vice versa. f) Regulation of emotion, either in the sense of emotional matching or of emotional attunement, proved to be the underlying motivating principle for both parental and infant imitations.The implications of these findings for understanding universal intersubjective nature of early imitation in infant -father and infant-mother interactions are discussed

    Toward an affect-sensitive multimodal human-computer interaction

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    The ability to recognize affective states of a person... This paper argues that next-generation human-computer interaction (HCI) designs need to include the essence of emotional intelligence -- the ability to recognize a user's affective states -- in order to become more human-like, more effective, and more efficient. Affective arousal modulates all nonverbal communicative cues (facial expressions, body movements, and vocal and physiological reactions). In a face-to-face interaction, humans detect and interpret those interactive signals of their communicator with little or no effort. Yet design and development of an automated system that accomplishes these tasks is rather difficult. This paper surveys the past work in solving these problems by a computer and provides a set of recommendations for developing the first part of an intelligent multimodal HCI -- an automatic personalized analyzer of a user's nonverbal affective feedback

    A critical evaluation of recent research into semantic development in child language

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    Bibliography: pages 166-172.This study examines critically recent research in the area of child language development, with an emphasis on research into semantic development. Various research articles, in particular, are analysed, with particular attention being given to experimental studies. In addition, research into language development in the naturalistic mode is discussed. The validity of research into language development in experimental contexts is questioned. Specific methods employed in experimental studies of language development are discussed critically. These methods are contrasted with methods used in a number of naturalistic studies. Recent research into semantic development is placed in the perspective of the study of semantics as a whole. The principal finding of this study is that research into language development in artificial experimental settings does not allow for valid conclusions to be drawn. Naturalistic studies are preferred in that they allow for language development, and semantic development in particular, to be placed in the context of overall child development. Language development is not able to be abstracted, for research purposes, from the totality of human development. Semantic development is viewed as a continuous process, lasting well into adulthood. The importance of the study of semantic development as part of semantics is emphasised

    Designing Sound for Social Robots: Advancing Professional Practice through Design Principles

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    Sound is one of the core modalities social robots can use to communicate with the humans around them in rich, engaging, and effective ways. While a robot's auditory communication happens predominantly through speech, a growing body of work demonstrates the various ways non-verbal robot sound can affect humans, and researchers have begun to formulate design recommendations that encourage using the medium to its full potential. However, formal strategies for successful robot sound design have so far not emerged, current frameworks and principles are largely untested and no effort has been made to survey creative robot sound design practice. In this dissertation, I combine creative practice, expert interviews, and human-robot interaction studies to advance our understanding of how designers can best ideate, create, and implement robot sound. In a first step, I map out a design space that combines established sound design frameworks with insights from interviews with robot sound design experts. I then systematically traverse this space across three robot sound design explorations, investigating (i) the effect of artificial movement sound on how robots are perceived, (ii) the benefits of applying compositional theory to robot sound design, and (iii) the role and potential of spatially distributed robot sound. Finally, I implement the designs from prior chapters into humanoid robot Diamandini, and deploy it as a case study. Based on a synthesis of the data collection and design practice conducted across the thesis, I argue that the creation of robot sound is best guided by four design perspectives: fiction (sound as a means to convey a narrative), composition (sound as its own separate listening experience), plasticity (sound as something that can vary and adapt over time), and space (spatial distribution of sound as a separate communication channel). The conclusion of the thesis presents these four perspectives and proposes eleven design principles across them which are supported by detailed examples. This work contributes an extensive body of design principles, process models, and techniques providing researchers and designers with new tools to enrich the way robots communicate with humans
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