@article{17265, abstract = {{Forty children, aged 1;8-2;0, participated in one of three training conditions meant to enhance their comprehension of the spatial term under: the +Gesture group viewed a symbolic gesture for under during training; those in the +Photo group viewed a still photograph of objects in the under relationship; those in the Model Only group did not receive supplemental symbolic support. Children's knowledge of under was measured before, immediately after, and two to three days after training. A gesture advantage was revealed when the gains exhibited by the groups on untrained materials (but not trained materials) were compared at delayed post-test (but not immediate Post-test). Gestured input promoted more robust knowledge of the meaning of under, knowledge that was less tied to contextual familiarity and more prone to consolidation. Gestured input likely reduced cognitive load while emphasizing both the location and the movement relevant to the meaning of under.}}, author = {{McGregor, Karla K. and Rohlfing, Katharina and Bean, Allison and Marschner, Ellen}}, issn = {{1469-7602}}, journal = {{JOURNAL OF CHILD LANGUAGE}}, number = {{04}}, pages = {{807--828}}, publisher = {{Cambridge University Press (CUP)}}, title = {{{Gesture as a support for word learning: The case of under}}}, doi = {{10.1017/S0305000908009173}}, volume = {{36}}, year = {{2009}}, } @article{17271, author = {{Booth, A. E and McGregor, Karla K. and Rohlfing, Katharina}}, issn = {{1547-3341}}, journal = {{Journal of Language Learning and Development}}, number = {{3}}, pages = {{179--202}}, publisher = {{Informa UK Limited}}, title = {{{Socio-pragmatics and attention: Contributions to gesturally guided word learning in toddlers}}}, doi = {{10.1080/15475440802143091}}, volume = {{4}}, year = {{2009}}, } @inproceedings{17268, author = {{Schillingmann, Lars and Wrede, Britta and Rohlfing, Katharina}}, booktitle = {{International Conference on Development and Learning (ICDL 2009)}}, isbn = {{978-1-4244-4117-4}}, keywords = {{Acoustic Packaging, multimodal}}, publisher = {{IEEE}}, title = {{{Towards a Computational Model of Acoustic Packaging}}}, doi = {{10.1109/devlrn.2009.5175523}}, year = {{2009}}, } @inproceedings{17266, author = {{Schillingmann, Lars and Wrede, Britta and Rohlfing, Katharina and Fischer, Kerstin}}, booktitle = {{Spoken Dialogue and Human-Robot Interaction}}, publisher = {{International Computer Science Institute}}, title = {{{The Structure of Robot-Directed Interaction compared to Adult- and Infant-Directed Interaction using a Model for Acoustic Packaging}}}, year = {{2009}}, } @inproceedings{17267, author = {{Lohse, Manja and Hanheide, Marc and Rohlfing, Katharina and Sagerer, Gerhard}}, booktitle = {{Proceedings of the 4th ACM/IEEE international conference on Human robot interaction - HRI '09}}, keywords = {{SINA, human robot interaction, biron}}, pages = {{93--100}}, title = {{{Systemic interaction analysis (SInA) in HRI}}}, doi = {{10.1145/1514095.1514114}}, year = {{2009}}, } @inproceedings{17270, author = {{Vollmer, Anna-Lisa and Lohan, Katrin Solveig and Fritsch, Jannik and Wrede, Britta and Rohlfing, Katharina}}, keywords = {{Contingency, Motionese}}, title = {{{Which Motionese Parameters Change with Children’s Age?}}}, year = {{2009}}, } @inproceedings{17263, author = {{Schillingmann, Lars and Wrede, Britta and Rohlfing, Katharina}}, booktitle = {{HUROBINT2009}}, title = {{{Acoustic Packaging}}}, year = {{2009}}, } @inproceedings{17275, abstract = {{How to teach actions to a robot as well as how a robot learns actions is an important issue to be discussed in designing robot learning systems. Inspired by human parent-infant interaction, we hypothesize that a robot equipped with infant-like abilities can take advantage of parental proper teaching. Parents are known to significantly alter their infant-directed actions versus adult-directed ones, e.g. make more pauses between movements, which is assumed to aid the infants’ understanding of the actions. As a first step, we analyzed parental actions using a primal attention model. The model based on visual saliency can detect likely important locations in a scene without employing any knowledge about the actions or the environment. Our statistical analysis revealed that the model was able to extract meaningful structures of the actions, e.g. the initial and final state of the actions and the significant state changes in them, which were highlighted by parental action modifications. We further discuss the issue of designing an infant-like robot that can induce parent-like teaching, and present a human-robot interaction experiment evaluating our robot simulation equipped with the saliency model.}}, author = {{Nagai, Yukie and Muhl, Claudia and Rohlfing, Katharina}}, booktitle = {{The 2008 IEEE International Conference on Robotics and Automation}}, keywords = {{icra08}}, pages = {{3545--3550}}, title = {{{Toward Designing a Robot that Learns Actions from Parental Demonstrations}}}, doi = {{10.1109/robot.2008.4543753}}, year = {{2008}}, } @inproceedings{17278, abstract = {{This paper investigates the influence of feedback provided by an autonomous robot (BIRON) on users’ discursive behavior. A user study is described during which users show objects to the robot. The results of the experiment indicate, that the robot’s verbal feedback utterances cause the humans to adapt their own way of speaking. The changes in users’ verbal behavior are due to their beliefs about the robots knowledge and abilities. In this paper they are identified and grouped. Moreover, the data implies variations in user behavior regarding gestures. Unlike speech, the robot was not able to give feedback with gestures. Due to the lack of feedback, users did not seem to have a consistent mental representation of the robot’s abilities to recognize gestures. As a result, changes between different gestures are interpreted to be unconscious variations accompanying speech.}}, author = {{Lohse, Manja and Rohlfing, Katharina and Wrede, Britta and Sagerer, Gerhard}}, isbn = {{1050-4729}}, keywords = {{discursive behavior, autonomous robot, BIRON, man-machine systems, robot abilities, robot knowledge, user gestures, robot verbal feedback utterance, speech processing, user verbal behavior, service robots, human-robot interaction, human computer interaction, gesture recognition}}, pages = {{3481--3486}}, title = {{{“Try something else!” — When users change their discursive behavior in human-robot interaction}}}, doi = {{10.1109/ROBOT.2008.4543743}}, year = {{2008}}, } @inproceedings{17273, abstract = {{Parents significantly alter their infant-directed actions compared to adult-directed ones, which is assumed to assist the infants’ processing of the actions. This paper discusses differences in parental action modification depending on whether the goal or the means is more crucial. When demonstrating a task to an infant, parents try to emphasize the important aspects of the task by suppressing or adding their movement. Our hypothesis is that in a goal-crucial task, the initial and final states of the task should be highlighted by parental actions, whereas in a means-crucial task the movement is underlined. Our analysis using a saliency-based attention model partially verified it: When focusing on the goal, parents tended to emphasize the initial and final states of the objects used in the task by taking a long pause before/after they started/fulfilled the task. When focusing on the means, parents shook the object to highlight it, which consequently made its state invisible. We discuss our findings regarding the uniqueness and commonality of the parental action modification. We also describe our contribution to the development of robots capable of imitating human actions.}}, author = {{Nagai, Yukie and Rohlfing, Katharina}}, booktitle = {{The IEEE 7th International Conference on Development and Learning}}, title = {{{Parental Action Modification Highlighting the Goal versus the Means}}}, doi = {{10.1109/devlrn.2008.4640796}}, year = {{2008}}, } @inbook{17277, author = {{Rohlfing, Katharina}}, booktitle = {{Handbook of Communication Competence}}, editor = {{Rickheit, G. and Strohner, H.}}, isbn = {{978-3-11-018829-5}}, pages = {{103--124}}, publisher = {{Mouton de Gruyter}}, title = {{{Cognitive Foundations}}}, year = {{2008}}, } @inproceedings{17274, author = {{Nagai, Yukie and Rohlfing, Katharina}}, booktitle = {{The 16th International Conference on Infant Studies}}, title = {{{Computational Analysis of Motionese: What can infants learn from parental actions?}}}, year = {{2008}}, } @inbook{17276, author = {{Rohlfing, Katharina}}, booktitle = {{The Bielefeld Introduction to Applied Linguistics}}, editor = {{Gramley, V.}}, title = {{{Language acquisition — a multimodal avenue}}}, year = {{2008}}, } @inbook{17280, abstract = {{Many classical approaches developed so far for learning in a human-robot interaction setting have focussed on rather low level motor learning by imitation. Some doubts, however, have been casted on whether with this approach higher level functioning will be achieved. Higher level processes include, for example, the cognitive capability to assign meaning to actions in order to learn from the tutor. Such capabilities involve that an agent not only needs to be able to mimic the motoric movement of the action performed by the tutor. Rather, it understands the constraints, the means and the goal(s) of an action in the course of its learning process. Further support for this hypothesis comes from parent-infant instructions where it has been observed that parents are very sensitive and adaptive tutors who modify their behavior to the cognitive needs of their infant. Based on these insights, we have started our research agenda on analyzing and modeling learning in a communicative situation by analyzing parent-infant instruction scenarios with automatic methods. Results confirm the well known observation that parents modify their behavior when interacting with their infant. We assume that these modifications do not only serve to keep the infant’s attention but do indeed help the infant to understand the actual goal of an action including relevant information such as constraints and means by enabling it to structure the action into smaller, meaningful chunks. We were able to determine first objective measurements from video as well as audio streams that can serve as cues for this information in order to facilitate learning of actions.}}, author = {{Wrede, Britta and Rohlfing, Katharina and Spexard, Thorsten P. and Fritsch, Jannik}}, booktitle = {{Humanoid Robots, Human-like Machines}}, editor = {{Hackel, Matthias}}, isbn = {{978-3-902613-07-3}}, pages = {{601--612}}, publisher = {{ARS}}, title = {{{Towards tutoring an interactive robot}}}, doi = {{10.5772/4825}}, year = {{2007}}, } @inproceedings{17279, abstract = {{An open question in imitating actions by infants and robots is how they know ‘‘what to imitate.’’ We suggest that parental modifications in their actions, called motionese, can help infants and robots to detect the meaningful structure of the actions. Parents tend to modify their infant-directed actions, e.g., put longer pauses between actions and exaggerate actions, which are assumed to help infants to understand the meaning and the structure of the actions. To investigate how such modifications contribute to the infants’ understanding of the actions, we analyzed parental actions from an infant-like viewpoint by applying a model of saliency-based visual attention. Our model of an infant-like viewpoint does not suppose any a priori knowledge about actions or objects used in the actions, or any specific capability to detect a parent’s face or his/her hands. Instead, it is able to detect and gaze at salient locations, which are standing out from the surroundings because of the primitive visual features, in a scene. The model thus demonstrates what low-level aspects of parental actions are highlighted in their action sequences and could attract the attention of young infants and robots. Our quantitative analysis revealed that motionese can help them (1) to receive immediate social feedback on the actions, (2) to detect the initial and goal states of the actions, and (3) to look at the static features of the objects used in the actions. We discuss these results addressing the issue of ‘‘what to imitate.’’}}, author = {{Nagai, Yukie and Rohlfing, Katharina}}, booktitle = {{The 4th International Symposium on Imitation in Animals and Artifacts}}, title = {{{Can Motionese Tell Infants and Robots "What to Imitate"?}}}, year = {{2007}}, } @inproceedings{17285, abstract = {{Whether interacting with a colleague from another department, a child with distinct cognitive and linguistic skills or a foreigner with different cultural background, humans try to adapt to their communication partners. The adaptation allows for a flow in communication and thereby for successful turn-taking. In contrast, when users communicate with artificial systems often reduced flow and turn-overtaking 4 are observable. The reasons for these insufficiencies may lie in the fact that little is known about the turn-taking strategies that dialogue systems should pursue 4. In our approach, we postulate that it is the feedback of the system and the interpretation of the feedback by the user that are in the center of an adaptation process As a result, one way to improve HRI, and especially its communicational flow, is to focus on different types of feedback and how they affect the user{\textquoteright} discursive behavior. In contrast to former work concentrating on telephone based speech systems or multimodal systems consisting of a touch screen and speech 1, 2, 5, we study an embodied interaction with the service robot BIRON (BIelefeld RObot CompanioN). The general goal of the studies is to develop a situated system that can learn the spatial environment as well as the names and visual appearance of objects. Therefore, BIRON can not only understand spoken speech but also co-verbal deictic references to objects in the scene and carry out mixed-initiative dialogues. In our study, the subjects were asked to introduce objects to the robot by showing and pointing. This very restricted goal allowed us to compare verbal and gestural behavior across subjects. We analyzed the interactions of 15 native German speaking users communicating with BIRON. The interaction was carried out with the fully autonomous mode of BIRON, except for the speech recognition, which was simulated by keyboard input in order to avoid speech recognition errors. By using the autonomous interaction system, we were able to produce realistic communication sequences including problems caused by the complex interaction of the diverse perceptual system components. In analyzing the users{\textquoteright} discursive behavior, we noticed different task-related interaction strategies. Focusing on subject{\textquoteright}s consistency and changes of strategies in the course of the ongoing turn-taking, we analyzed which feedback of the system caused a change of a strategy within a user. We found that subjects decided for one strategy addressing one perceptual channel (vision or speech) of the system and used it as long as they did not receive any feedback about the failure of this specific channel. We observed a change in strategy when it became obvious to the subject via feedback that a particular perceptual channel was not working appropriately. The change in strategy was likely to maintain the interaction flow and thereby the user satisfaction. While these results support previous findings indicating when and how users change strategies 1, 5, they give new insights into the discursive behavior, i.e. into the repertoire of strategies in embodied and situated interaction. The results imply that within turn-taking, users interpret the system{\textquoteright}s feedback and thus verify their model of the capabilities of the interlocutor. Thus, the change in discursive strategy is an indicator of users{\textquoteright} expectation of how the robot functions 3. In further studies we plan to deliberately vary the robots misunderstandings and integrate the personality traits of the subjects into the research on strategies.}}, author = {{Lohse, Manja and Rohlfing, Katharina and Wrede, Britta}}, booktitle = {{Presentation at the 10th International Pragmatics Conference (IPrA)}}, title = {{{Changes of users' discursive behavior in HRI}}}, year = {{2007}}, } @inproceedings{17284, abstract = {{The paper introduces an online user study onapplications for social robots with 127 participants. The potential users proposed 570 application scenarios based on the appearance and functionality of four robots presented (AIBO,BARTHOC, BIRON, iCat). The items were grouped into 13 categories which are interpreted and discussed by means of four dimensions: public vs. private use, intensity of interaction,complexity of interaction model, and functional vs. human-like appearance. The interpretation lead to three classes of applications for social robots according to the degree of social interaction: (1) Specialized Applications where the robot has to perform clearly defined tasks which are delegated by a user, (2)Public Applications which are directed to the communication with many users, and (3) Individual Applications with the need of a highly elaborated social model to maintain a variety of situations with few people.}}, author = {{Hegel, Frank and Lohse, Manja and Swadzba, Agnes and Wachsmuth, Sven and Rohlfing, Katharina and Wrede, Britta}}, booktitle = {{16th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN’07)}}, pages = {{938--943}}, publisher = {{IEEE}}, title = {{{Classes of Applications for Social Robots: A User Study}}}, doi = {{10.1109/roman.2007.4415218}}, year = {{2007}}, } @inproceedings{17282, abstract = {{In recent years industrial robots have been successfully established because they fulfil meaningful tasks in production. In contrast the question of applications for social robots is still open. For quite some time they have only been used in research or at best as simple toys by real users in everyday life situations. However, we suggest that there are still unknown application fields that are suitable for existing robots. Therefore, our approach is to show short movies and descriptions of real robots to participants and ask whether there are any specific tasks these robots could perform in the naive users' everyday life. The systems' appearance and abilities strongly influence the user's expectations, that's why we suppose that we will find strong differences between zoomorphic robots like AIBO and iCat and other robots like BIRON (functional design) and BARTHOC (humanoid). We have conducted an online study with more than 100 participants to test this hypothesis.}}, author = {{Lohse, Manja and Hegel, Frank and Swadzba, Agnes and Rohlfing, Katharina and Wachsmuth, Sven and Wrede, Britta}}, booktitle = {{Workshop on The Reign of Catz and Dogz? The role of virtual creatures in a computerised society}}, pages = {{121--126}}, title = {{{What can I do for you? Appearance and Application of Robots}}}, year = {{2007}}, } @inproceedings{17283, abstract = {{This paper presents a new insight from a computational analysis of parental actions. Developmental behavioral studies have suggested that parental modifications in their actions directed to infants versus to adults may aid the infants’ processing of the actions. We have been analyzing parental actions using a bottom-up attention model so as to take the advantage in robot action learning. Our latest result indicates that parental social signals can be used for a robot to detect significant state changes in the demonstrated action.}}, author = {{Nagai, Yukie and Rohlfing, Katharina}}, booktitle = {{The 7th International Conference on Epigenetic Robotics}}, title = {{{Parental Signal Indicating Significant State Change in Action Demonstration}}}, year = {{2007}}, } @inproceedings{17281, author = {{Rohlfing, Katharina and Kopp, Stefan}}, booktitle = {{Proc. Symposium on Language & Robots}}, pages = {{79--82}}, title = {{{Meaning in the timing? The emergence of complex pointing patterns}}}, year = {{2007}}, }