People Interpret Robotic Non-linguistic Utterances Categorically

We present results of an experiment probing whether adults exhibit categorical perception when affectively rating robot-like sounds (Non-linguistic Utterances). The experimental design followed the traditional methodology from the psychology domain for measuring categorical perception: stimulus continua for robot sounds were presented to subjects, who were asked to complete a discrimination and an identification task. In the former subjects were asked to rate whether stimulus pairs were affectively different, while in the latter they were asked to rate single stimuli affectively. The experiment confirms that Non-linguistic Utterances can convey affect and that they are drawn towards prototypical emotions, confirming that people show categorical perception at a level of inferred affective meaning when hearing robot-like sounds. We speculate on how these insights can be used to automatically design and generate affect-laden robot-like utterances

Modelling emotional valence and arousal of non-linguistic utterances for sound design support

Non-Linguistic Utterances (NLUs), produced for popular media, computers, robots, and public spaces, can quickly and wordlessly convey emotional characteristics of a message. They have been studied in terms of their ability to convey affect in robot communication. The objective of this research is to develop a model that correctly infers the emotional Valence and Arousal of an NLU. On a Likert scale, 17 subjects evaluated the relative Valence and Arousal of 560 sounds collected from popular movies, TV shows, and video games, including NLUs and other character utterances. Three audio feature sets were used to extract features including spectral energy, spectral spread, zero-crossing rate (ZCR), Mel Frequency Cepstral Coefficients (MFCCs), and audio chroma, as well as pitch, jitter, formant, shimmer, loudness, and Harmonics-to-Noise Ratio, among others. After feature reduction by Factor Analysis, the best-performing models inferred average Valence with a Mean Absolute Error (MAE) of 0.107 and Arousal with MAE of 0.097 on audio samples removed from the training stages. These results suggest the model infers Valence and Arousal of most NLUs to less than the difference between successive rating points on the 7-point Likert scale (0.14). This inference system is applicable to the development of novel NLUs to augment robot-human communication or to the design of sounds for other systems, machines, and settings

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

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

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

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

Non-verbal auditory aspects of human-service robot interaction

As service robots become ever more pervasive, the number, degree and depth of interaction with humans, particularly fellow workers, is increasing rapidly. Humans are generally shaped alike, respond in predominantly similar ways and are often inherently predictable to other humans. Robots, by contrast, have an exceptional diversity of size, shape, mobility, function, and their intentions or actions are often less predictable. Humans working in close proximity have learnt to provide cues to their behaviour, both verbal and non-verbal, and we argue that this is an important aspect of maintaining both safety and comfort in a mixed work or social environment. At present, robots do not provide any such cues to their fellow workers, which can be cause of human discomfort, and indeed contribute to safety issues when working in close proximity to humans. This paper considers the non-verbal auditory aspects of interaction in a work environment, with particular emphasis on safe and comfortable integration of service robots into such locations. In particular, we propose a classification of interaction levels to inform the construction, programming and operation of robots in the workplace

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

Wyłanianie się komunikacji: argument z robotyki

Some “traditional” issues in language emergence and development are viewed through the prism of the interaction of autonomous robots with their environment and through their communicative skills based on the signaling system which emerges as a result of the robots’ own evolution. The main goal of the paper is to present initial conditions necessary for the emergence of communication in a group of robots. First, the paper discusses, in relation to the general faculty of language, the change that has taken place within cognitive science, particularly within computational modelling and Artificial Intelligence. Then a number of basic, individual cognitive mechanisms (pre-adaptations) are suggested, including the robots’ ability to distinguish signals, associate them with particular situations and imitate signaling behavior. These basic individual abilities may develop in the context of a community of interacting agents as well as in the changing communicative environment. In order to practice and develop the cognitive capacities, robotic agents are expected to engage in a number of activities ('language games'), including the imitation of actions, the negotiation of reference and the use of signals in the absence of referents. Inquiries into the emergence of communication in natural and artificial systems can help isolate the possible stages of the development of the robots’ communicative abilities.Niektóre „tradycyjne” kwestie związane z wyłanianiem się i rozwojem języka mogą być rozpatrywane w perspektywnie autonomicznych robotów, ich interakcji ze środowiskiem oraz ich zdolności komunikacyjnych opartych na systemie sygnałów, wyłaniającym się w toku ewolucji robotów. Głównym celem artykułu jest przedstawienie podstawowych, minimalnych zdolności niezbędnych do wyłonienia się komunikacji w grupie robotów. Na początku zarysowana została zmiana, jaka zaszła w podejściu do modelowania języka w kognitywistyce i w szczególności w kognitywistycznych badaniach nad sztuczną inteligencją. W dalszej części zaprezentowano przypuszczalne podstawowe mechanizmy poznawcze, w jakie powinien być wyposażony indywidualny robot, mianowicie: zdolność do rozróżniania sygnałów, do kojarzenia ich z konkretnymi sytuacjami oraz do naśladowania zachowań sygnalizacyjnych. Te podstawowe indywidualne zdolności mogą się rozwijać w ramach grupy współdziałających robotów osadzonych w zmieniającym się środowisku. By przećwiczyć te zdolności i je rozwinąć, roboty biorą udział w serii narzuconych przez eksperymentatora zadań („gier językowych”), takich jak: naśladowanie działań, negocjacje odniesienia, używanie sygnałów przy braku referenta tych sygnałów. Badania nad wyłanianiem się komunikacji w społecznościach naturalnych i sztucznych systemów mogą pomóc w identyfikacji etapów rozwoju zdolności komunikacyjnych

A Review of Possible EEG Markers of Abstraction, Attentiveness and Memorisation in Cyber-Physical Systems for Special Education

[EN]Cyber-physical systems (CPSs) for special education rely on effective mental and brain processing during the lesson, performed with the assistance of humanoid robots. The improved diagnostic ability of the CPS is a prerogative of the system for efficient technological support of the pedagogical process. The article focuses on the available knowledge of possible EEG markers of abstraction, attentiveness, and memorisation (in some cases combined with eye tracking) related to predicting effective mental and brain processing during the lesson. The role of processing abstraction is emphasised as the learning mechanism, which is given priority over the other mechanisms by the cognitive system. The main markers in focus are P1, N170, Novelty P3, RewP, N400, and P600. The description of the effects is accompanied by the analysis of some implications for the design of novel educational scenarios in inclusive classes.The presented research received funding from the EC for project CybSPEED,. 777720, H2020-MSCA-RISE-2017; the Bulgarian Research Fund project,. KP-06-H42/4 (2020-2023); and the project Competence Center "Intelligent mechatronic, eco-and energy saving systems and technologies". BG05M2OP0011.002-0023, OP Science and Education for Smart Growth (2014-2020)

Conversation and Its Erosion Into Discourse and Computation

In my answer to Ernst von Glasersfeld\u27s (2008) question Who conceives Society? I proposed a radically social constructivism (Krippendorff, 2008a) that overcomes what I perceive to be an unfortunate cognitivism in von Glasersfeld\u27s, Heinz von Foerster\u27s, and Humberto Maturana\u27s work. Since then, I published two other papers on the subject. One (2008b) moves the notion of human agency into the center of my project, focusing on its role in conceptions of social organizations - a concept less grand than society and one (2008c) teases out several reflexive turns that have grown in cybernetics but cannot be subsumed by the epistemology of radical constructivism and second-order cybernetics, which privileges observation and a representational theory of language over participation in conversation and cooperative constructions of reality. In all of these efforts, conversation has become the starting point of my conceptualizations of being human. In this essay, I wish to discuss what conversation entails, how it is maintained, and under which conditions it degenerates into something else