@article{17238, author = {{Rohlfing, Katharina and Wrede, Britta}}, journal = {{The Newsletter of the Autonomous Mental Development Technical Committee}}, number = {{2}}, pages = {{11--13}}, title = {{{What novel scientific and technological questions developmental robotics bring to HRI? — Are we ready for a loop?}}}, volume = {{8}}, year = {{2011}}, } @inbook{17241, author = {{Rohlfing, Katharina}}, booktitle = {{Experimental Pragmatics/Semantics}}, editor = {{Meibauer, J. and Steinbach, M.}}, pages = {{151--176}}, publisher = {{Benjamins}}, title = {{{Meaning in the objects}}}, year = {{2011}}, } @inproceedings{17232, author = {{Hemion, Nikolas and Joublin, Frank and Rohlfing, Katharina}}, booktitle = {{2011 IEEE International Conference on Development and Learning (ICDL)}}, publisher = {{IEEE}}, title = {{{A competitive mechanism for self-organized learning of sensorimotor mappings}}}, doi = {{10.1109/DEVLRN.2011.6037364}}, year = {{2011}}, } @inproceedings{17255, abstract = {{In recent years, research has moved towards the learning by interaction paradigm 1 suggesting that interaction with an artificial agent is facilitated when characteristics of a social interaction are considered. It is envisoned that agents will learn from humans by simply interacting with each other. In such a scenario, learning by interaction {\textquoteright}goes beyond common supervised or unsupervised strategies by taking into account wider feedback and assessments for the learning processes{\textquoteright} (1 p.140). So far, little is known about interactional processes and feedback strategies involved. Yet, in order to learn, a learner will typically need to be provided with information given by a teacher who not only gives certain structure to the interaction but also instructs for and demonstrates the learning contents. The given information can only be effective, if the learner is receptive. To assure this, the tutor makes use of interactive regularities checking the learner{\textquoteright}s behavior. The term contingency has been suggested to encompass such regu- larities in interaction. More specifically, it refers to a temporal sequence of behavior and reaction (2, 3). It has been shown that contingency is an important factor in interactions with infants and contributes to the cognitive development of infants 4. In the interaction with an artificial agent, contingency has been operationalized by eye-gaze bouts 5. So far, it has been shown that while in a situation with a child, eye-gaze bouts in total, average and frequency is much higher as in interaction with an adult as learner. In a situation with an artificial agent, a decrease of eye-gaze bouts could be observed 5. It could thus be reasoned that tutor{\textquoteright}s monitoring behavior is impaired when interacting with a robot. However, so far only an interaction with a virtual robot has been investigated. In contrast, an embodied robot could evoke a more natural tutor behavior. In this study, we therefore investigated a tutoring situation with an embodied robot and focused on tutor{\textquoteright}s monitoring behavior. We followed the minimal definition of embodiment by K. Dautenhahn et al. to quantify the difference in embodiment between these two systems 6. Accordingly, the Degrees of Embodiment (DOM) are calculated as:DOMS,E = f (x, y, t), where system S in respect to an environment E is calculated by a function f of the vectors x and y and the time t. x describes the number of sensors, the detected modalities of the sensors and the channels of information provided by the sensors, y describes the degree of freedom (DoF) of the robot. In our experiments E remained unchanged and thus the DOM is not affected by this factor. We argue that in our case, the function f is only dependent on the degrees of freedom of the robot. Possibly, we can give a value which represents the difference in the degree of embodiment (DDOM). Since our goal was to study some characteristics of contingency (7, 5), our dependent variable was the tutor{\textquoteright}s monitoring behavior operationalized by the eye-gaze.}}, author = {{Lohan, Katrin Solveig and Gieselmann, Sebastian and Vollmer, Anna-Lisa and Rohlfing, Katharina and Wrede, Britta}}, booktitle = {{International Conference on Development and Learning}}, publisher = {{IEEE}}, title = {{{Does embodiment affect tutoring behavior?}}}, year = {{2010}}, } @article{17256, author = {{Grimminger, Angela and Rohlfing, Katharina and Stenneken, Prisca}}, issn = {{1569-9773}}, journal = {{Gesture}}, keywords = {{task- oriented dialogue, Late Talker, maternal multimodal input, gestural motherese}}, number = {{2}}, pages = {{251--278}}, publisher = {{John Benjamins Publishing Company}}, title = {{{Children's lexical skills and task demands affect gestural behavior in mothers of late-talking children and children with typical language development}}}, doi = {{10.1075/gest.10.2-3.07gri}}, volume = {{10}}, year = {{2010}}, } @article{17254, author = {{Rohlfing, Katharina and Wrede, Britta}}, issn = {{1571-0645}}, journal = {{PHYSICS OF LIFE REVIEWS}}, number = {{2}}, pages = {{152--153}}, publisher = {{Elsevier BV}}, title = {{{From action to language and back Comment on 'Grounding language in action and perception: From cognitive agents to humanoid robots' by Cangelosi}}}, doi = {{10.1016/j.plrev.2010.04.002}}, volume = {{7}}, year = {{2010}}, } @article{20253, author = {{Cangelosi, Angelo and Metta, Giorgio and Sagerer, Gerhard and Nolfi, Stefano and Nehaniv, Chrystopher and Fischer, Kerstin and Tani, Jun and Belpaeme, Tony and Sandini, Giulio and Nori, Francesco and Fadiga, Luciano and Wrede, Britta and Rohlfing, Katharina and Tuci, Elio and Dautenhahn, Kerstin and Saunders, Joe and Zeschel, Arne}}, issn = {{1943-0604}}, journal = {{IEEE Transactions on Autonomous Mental Development}}, pages = {{167--195}}, title = {{{Integration of Action and Language Knowledge: A Roadmap for Developmental Robotics}}}, doi = {{10.1109/tamd.2010.2053034}}, year = {{2010}}, } @article{17250, abstract = {{Based on the observation that human-robot interaction is often laborious because the robot's interactional abilities fail to meet the user's expectations, we argue that feedback can play a central role in regulating expectations and mitigating unnecessary disruptions in the flow of conversation. For feedback to be appropriate in this sense, it needs to take situational information into account. This idea stems from interviews with persons with hearing and mental impairments who display perceptual limitations similar to a robot. The results of these interviews indicated that, depending on the goals of the situation, people with hearing impairments used either mediation (clarification) or concealment strategies to keep the interaction going. With this idea in mind, we analyzed human-robot interactions in two different situations - more task-oriented interactions versus more socially driven interactions - and we observed different feedback behaviors in users and their reactions to the robot's behavior. We use these results to derive a scaffold for modeling appropriate feedback in asymmetric interactions (i.e., in human-robot interactions) and briefly discuss some consequences for both the design of human-robot interaction and for theories of grounding. (c) 2010 Elsevier B.V. All rights reserved.}}, author = {{Wrede, Britta and Kopp, Stefan and Rohlfing, Katharina and Lohse, Manja and Muhl, Claudia}}, issn = {{0378-2166}}, journal = {{Journal of Pragmatics}}, number = {{9}}, pages = {{2369--2384}}, publisher = {{Elsevier }}, title = {{{Appropriate Feedback in Asymmetric Interactions}}}, doi = {{10.1016/j.pragma.2010.01.003}}, volume = {{42}}, year = {{2010}}, } @inproceedings{17253, author = {{Vollmer, Anna-Lisa and Pitsch, Karola and Lohan, Katrin Solveig and Fritsch, Jannik and Rohlfing, Katharina and Wrede, Britta}}, booktitle = {{Development and Learning (ICDL), 2010 IEEE 9th International Conference on Development and Learning}}, keywords = {{tutoring interaction, social interaction, video signal processing, robot systems, paediatrics, neurophysiology, Learning, infant, feedback, biology computing, cognitive capabilities, cognition, children}}, pages = {{76--81}}, title = {{{Developing feedback: How children of different age contribute to a tutoring interaction with adults}}}, year = {{2010}}, } @inproceedings{17252, author = {{Choi, Soonja and Rohlfing, Katharina}}, booktitle = {{Japanese / Korean Linguistics}}, editor = {{Iwasaki, S. and Hoji, H. and Clancy, P. M and Sohn, S.-O.}}, pages = {{117--133}}, publisher = {{CSLI Publications}}, title = {{{Discourse and lexical patterns in mothers' speech during spatial tasks: What role do spatial words play?}}}, volume = {{17}}, year = {{2010}}, } @inproceedings{17251, author = {{Nomikou, Iris and Rohlfing, Katharina}}, title = {{{Exploring vocal-motor synchrony: Maternal intermodal synchrony and rhythmic patterning of interactions with 3-4 month olds.}}}, year = {{2010}}, } @article{17258, abstract = {{In order to learn and interact with humans, robots need to understand actions and make use of language in social interactions. The use of language for the learning of actions has been emphasized by Hirsh-Pasek and Golinkoff (MIT Press, 1996), introducing the idea of acoustic packaging. Accordingly, it has been suggested that acoustic information, typically in the form of narration, overlaps with action sequences and provides infants with a bottom-up guide to attend to relevant parts and to find structure within them. In this article, we present a computational model of the multimodal interplay of action and language in tutoring situations. For our purpose, we understand events as temporal intervals, which have to be segmented in both, the visual and the acoustic modality. Our acoustic packaging algorithm merges the segments from both modalities based on temporal overlap. First evaluation results show that acoustic packaging can provide a meaningful segmentation of action demonstration within tutoring behavior. We discuss our findings with regard to a meaningful action segmentation. Based on our future vision of acoustic packaging we point out a roadmap describing the further development of acoustic packaging and interactive scenarios it is employed in.}}, author = {{Schillingmann, Lars and Wrede, Britta and Rohlfing, Katharina}}, issn = {{1943-0612}}, journal = {{IEEE Transactions on Autonomous Mental Development}}, number = {{4}}, pages = {{226--237}}, publisher = {{Institute of Electrical & Electronics Engineers (IEEE)}}, title = {{{A Computational Model of Acoustic Packaging}}}, doi = {{10.1109/TAMD.2009.2039135}}, volume = {{1}}, year = {{2009}}, } @inproceedings{17259, abstract = {{Learning is a social endeavor, in which the learner generally receives support from his/her social partner(s). In developmental research – even though tutors/adults behavior modifications in their speech, gestures and motions have been extensively studied, studies barely consider the recipient’s (i.e. the child’s) perspective in the analysis of the adult’s presentation, In addition, the variability in parental behavior, i.e. the fact that not every parent modifies her/his behavior in the same way, found less fine-grained analysis. In contrast, in this paper, we assume an interactional perspective investigating the loop between the tutor’s and the learner’s actions. With this approach, we aim both at discovering the levels and features of variability and at achieving a better understanding of how they come about within the course of the interaction. For our analysis, we used a combination of (1) qualitative investigation derived from ethnomethodological Conversation Analysis (CA), (2) semi-automatic computational 2D hand tracking and (3) a mathematically based visualization of the data. Our analysis reveals that tutors not only shape their demonstrations differently with regard to the intended recipient per se (adult-directed vs. child-directed), but most importantly that the learner’s feedback during the presentation is consequential for the concrete ways in which the presentation is carried out.}}, author = {{Pitsch, Karola and Vollmer, Anna-Lisa and Fritsch, Jannik and Wrede, Britta and Rohlfing, Katharina and Sagerer, Gerhard}}, booktitle = {{Gesture and Speech in Interaction}}, keywords = {{gaze, gesture, Multimodal, adult-child interaction}}, title = {{{On the loop of action modification and the recipient's gaze in adult-child interaction}}}, year = {{2009}}, } @article{17262, abstract = {{A difficulty in robot action learning is that robots do not know where to attend when observing action demonstration. Inspired by human parent-infant interaction, we suggest that parental action demonstration to infants, called motionese, can scaffold robot learning as well as infants. Since infants knowledge about the context is limited, which is comparable to robots, parents are supposed to properly guide their attention by emphasizing the important aspects of the action. Our analysis employing a bottom-up attention model revealed that motionese has the effects of highlighting the initial and final states of the action, indicating significant state changes in it, and underlining the properties of objects used in the action. Suppression and addition of parents body movement and their frequent social signals to infants produced these effects. Our findings are discussed toward designing robots that can take advantage of parental teaching.}}, author = {{Nagai, Yukie and Rohlfing, Katharina}}, issn = {{1943-0612}}, journal = {{IEEE Transactions on Autonomous Mental Development}}, number = {{1}}, pages = {{44--54}}, publisher = {{Institute of Electrical & Electronics Engineers (IEEE)}}, title = {{{Computational Analysis of Motionese Toward Scaffolding Robot Action Learning}}}, doi = {{10.1109/TAMD.2009.2021090}}, volume = {{1}}, year = {{2009}}, } @article{17260, author = {{Lohse, Manja and Hanheide, Marc and Pitsch, Karola and Rohlfing, Katharina and Sagerer, Gerhard}}, issn = {{1572-0381}}, journal = {{Interaction Studies (Special Issue: Robots in the Wild: Exploring HRI in naturalistic environments)}}, number = {{3}}, pages = {{298--323}}, publisher = {{John Benjamins Publishing Company}}, title = {{{Improving HRI design by applying Systemic Interaction Analysis (SInA)}}}, doi = {{10.1075/is.10.3.03loh}}, volume = {{10}}, year = {{2009}}, } @inproceedings{17257, abstract = {{In developmental research, tutoring behavior has been identified as scaffolding infants’ learning processes. It has been defined in terms of child-directed speech (Motherese), child-directed motion (Motionese), and contingency. Contingency describes situations in which two agents socially interact with each other and Csibra and Gergely showed that contingency is a char- acteristic aspect of social interaction [3]. In the field of developmental robotics, research often assumes that in human-robot interaction (HRI), robots are treated similar to infants, because their immature cognitive capabilities benefit from this behavior. Here we present results con- cerning the acceptance of a robotic agent in a social learning scenario obtained via comparison to adults and 8-11 months old infants in equal conditions. These results constitute an important empirical basis for making use of tutoring behavior in social robotics. Our results reveal significant differences between Adult-Child Interaction (ACI), Adult-Adult Interaction (AAI) and Adult-Robot Interaction (ARI) in eye gaze behavior suggesting that contingency is impaired in the analyzed ARI situation.}}, author = {{Lohan, Katrin Solveig and Rohlfing, Katharina and Wrede, Britta}}, keywords = {{Eyegaze, tutoring situations, Contingency}}, title = {{{Analysing the effect of contingency in tutoring situations}}}, year = {{2009}}, } @inbook{17261, author = {{Wrede, Britta and Rohlfing, Katharina and Hanheide, Marc and Sagerer, Gerhard}}, booktitle = {{Creating Brain-Like Intelligence: From Basic Principles to Complex Intelligent Systems}}, editor = {{Sendhoff, B. and Körner, Edgar and Sporns, O. and Ritter, Helge and Doya, Kenji}}, pages = {{139--150}}, publisher = {{Springer}}, title = {{{Towards Learning by Interacting}}}, doi = {{10.1007/978-3-642-00616-6_8}}, year = {{2009}}, } @inproceedings{17272, abstract = {{In developmental research, tutoring behavior has been identified as scaffolding infants' learning processes. It has been defined in terms of child-directed speech (Motherese), child-directed motion (Motionese), and contingency. In the field of developmental robotics, research often assumes that in human-robot interaction (HRI), robots are treated similar to infants, because their immature cognitive capabilities benefit from this behavior. However, according to our knowledge, it has barely been studied whether this is true and how exactly humans alter their behavior towards a robotic interaction partner. In this paper, we present results concerning the acceptance of a robotic agent in a social learning scenario obtained via comparison to adults and 8-11 months old infants in equal conditions. These results constitute an important empirical basis for making use of tutoring behavior in social robotics. In our study, we performed a detailed multimodal analysis of HRI in a tutoring situation using the example of a robot simulation equipped with a bottom-up saliency-based attention model. Our results reveal significant differences in hand movement velocity, motion pauses, range of motion, and eye gaze suggesting that for example adults decrease their hand movement velocity in an Adult-Child Interaction (ACI), opposed to an Adult-Adult Interaction (AAI) and this decrease is even higher in the Adult-Robot Interaction (ARI). We also found important differences between ACI and ARI in how the behavior is modified over time as the interaction unfolds. These findings indicate the necessity of integrating top-down feedback structures into a bottom-up system for robots to be fully accepted as interaction partners.}}, author = {{Vollmer, Anna-Lisa and Lohan, Katrin Solveig and Fischer, Kerstin and Nagai, Yukie and Pitsch, Karola and Fritsch, Jannik and Rohlfing, Katharina and Wrede, Britta}}, booktitle = {{Development and Learning, 2009. ICDL 2009. IEEE 8th International Conference on Development and Learning}}, keywords = {{robot simulation, hand movement velocity, robotic interaction partner, robotic agent, robot-directed interaction, multimodal analysis, Motionese, Motherese, intelligent tutoring systems, immature cognitive capability, human computer interaction, eye gaze, child-directed speech, child-directed motion, bottom-up system, bottom-up saliency-based attention model, adult-robot interaction, adult-child interaction, adult-adult interaction, human-robot interaction, action learning, social learning scenario, social robotics, software agents, top-down feedback structures, tutoring behavior}}, pages = {{1--6}}, publisher = {{IEEE}}, title = {{{People modify their tutoring behavior in robot-directed interaction for action learning}}}, doi = {{10.1109/DEVLRN.2009.5175516}}, year = {{2009}}, } @inproceedings{17264, abstract = {{In developmental research, tutoring behavior has been identified as scaffolding infants’ learning processes. Infants seem sensitive to tutoring situations and they detect these by ostensive cues [4]. Some social signals such as eye-gaze, child-directed speech (Motherese), child-directed motion (Motionese), and contingency have been shown to serve as ostensive cues. The concept of contingency describes exchanges in which two agents interact with each other reciprocally. Csibra and Gergely argued that contingency is a characteristic ostensive stimulus of a tutoring situation [4]. In order for a robot to be treated similar to an infant, it has to both, be sensitive to the ostensive stimuli on the one hand and induce tutoring behavior by its feedback about its capabilities on the other hand. In this paper, we raise the question whether a robot can be treated similar to an infant in an interaction. We present results concerning the acceptance of a robotic agent in a social learning scenario, which we obtained via comparison to interactions with 8-11 months old infants and adults in equal conditions. We applied measurements for motion modifications (Motionese) and eye-gaze behavior. Our results reveal significant differences between Adult-Child Interaction (ACI), Adult-Adult Interaction (AAI) and Adult- Robot Interaction (ARI) suggesting that in ARI, robotdirected tutoring behavior is even more accentuated in terms of Motionese, but contingent responsivity is impaired. Our results confirm previous findings [14] concerning the differences between ACI, AAI, and ARI and constitute an important empirical basis for making use of ostensive stimuli as social signals for tutoring behavior in social robotics.}}, author = {{Lohan, Katrin Solveig and Vollmer, Anna-Lisa and Fritsch, Jannik and Rohlfing, Katharina and Wrede, Britta}}, booktitle = {{IEEE International Workshop on Social Signal Processing}}, isbn = {{9781424448005}}, keywords = {{Ostensive Signals, Contingency, Motionese, hri}}, publisher = {{International Computer Science Institute}}, title = {{{Which ostensive stimuli can be used for a robot to detect and maintain tutoring situations?}}}, doi = {{10.1109/acii.2009.5349507}}, year = {{2009}}, } @article{17269, abstract = {{Infants learning about their environment are confronted with many stimuli of different modalities. Therefore, a crucial problem is how to discover which stimuli are related, for instance, in learning words. In making these multimodal "bindings," infants depend on social interaction with a caregiver to guide their attention towards relevant stimuli. The caregiver might, for example, visually highlight an object by shaking it while vocalizing the object's name. These cues are known to help structuring the continuous stream of stimuli. To detect and exploit them, we propose a model of bottom-up attention by multimodal signal-level synchrony. We focus on the guidance of visual attention from audio-visual synchrony informed by recent adult-infant interaction studies. Consequently, we demonstrate that our model is receptive to parental cues during child-directed tutoring. The findings discussed in this paper are consistent with recent results from developmental psychology but for the first time are obtained employing an objective, computational model. The presence of " multimodal motherese" is verified directly on the audio-visual signal. Lastly, we hypothesize how our computational model facilitates tutoring interaction and discuss its application in interactive learning scenarios, enabling social robots to benefit from adult-like tutoring. Document Type: Article}}, author = {{Rolf, Matthias and Hanheide, Marc and Rohlfing, Katharina}}, issn = {{1943-0612}}, journal = {{IEEE Transactions on Autonomous Mental Development}}, number = {{1}}, pages = {{55--67}}, publisher = {{Institute of Electrical & Electronics Engineers (IEEE)}}, title = {{{Attention via synchrony. Making use of multimodal cues in social learning}}}, doi = {{10.1109/TAMD.2009.2021091}}, volume = {{1}}, year = {{2009}}, }