Therapist-Centered Design of a Robot’s Dialogue Behavior

Significant research effort has already been invested in the field of robot-assisted therapy for children with developmental disorders, and the researchers generally agree that therapists should be involved in the development of assistive robotic tools. However, relatively little attention has been devoted to robots’ capacity to autonomously engage in a natural language dialogue in the context of robot-assisted therapy. This paper focuses on this desideratum. It introduces a programming platform that enables the therapist to design a robot’s dialogue behavior. To the extent that the platform is domain-independent, it enables the therapist to flexibly model (1) the interaction domain and the lexicon, (2) the interaction context, and (3) the robot’s dialogue strategy. To the extent that the platform is therapist-centered, it is motivated by real-life difficulties that therapists encounter while trying to specify a robot’s dialogue behavior and can be used by nontechnical therapists in a user-friendly and intuitive manner. In addition, the platform (4) enables the therapist to test dialogue strategies independently of therapeutic settings, and (5) provides estimated cognitive load placed on the child while trying to process the therapist’s dialogue acts.

[1]  Jose L Pons,et al.  Converging clinical and engineering research on neurorehabilitation , 2013 .

[2]  RobinsBen,et al.  KASPAR --a minimally expressive humanoid robot for human--robot interaction research , 2009 .

[3]  Caitlin Kelleher,et al.  Towards a therapist-centered programming environment for creating rehabilitation games , 2011, 2011 16th International Conference on Computer Games (CGAMES).

[4]  Daniel J. Ricks,et al.  Trends and considerations in robot-assisted autism therapy , 2010, 2010 IEEE International Conference on Robotics and Automation.

[5]  Klaus Oberauer,et al.  Activation and binding in verbal working memory: A dual-process model for the recognition of nonwords , 2009, Cognitive Psychology.

[6]  Maja J. Mataric,et al.  Using Socially Assistive Human–Robot Interaction to Motivate Physical Exercise for Older Adults , 2012, Proceedings of the IEEE.

[7]  Rodney A. Brooks,et al.  Humanoid robots , 2002, CACM.

[8]  E. Gibson Linguistic complexity: locality of syntactic dependencies , 1998, Cognition.

[9]  Vlado Delic,et al.  Focus tree: modeling attentional information in task-oriented human-machine interaction , 2012, Applied Intelligence.

[10]  N. Cowan Evolving conceptions of memory storage, selective attention, and their mutual constraints within the human information-processing system. , 1988, Psychological bulletin.

[11]  Michelle J Johnson,et al.  Recent trends in robot-assisted therapy environments to improve real-life functional performance after stroke , 2006, Journal of NeuroEngineering and Rehabilitation.

[12]  María Victoria Rodellar Biarge,et al.  Characterizing Neurological Disease from Voice Quality Biomechanical Analysis , 2013, Cognitive Computation.

[13]  Vlado Delic,et al.  End-User Design of Emotion-Adaptive Dialogue Strategies for Therapeutic Purposes , 2013, WIRN.

[14]  Timothy W. Bickmore,et al.  Establishing and maintaining long-term human-computer relationships , 2005, TCHI.

[15]  Emilia I. Barakova,et al.  End-user programming architecture facilitates the uptake of robots in social therapies , 2013, Robotics Auton. Syst..

[16]  Marcos Faúndez-Zanuy,et al.  Biometric Applications Related to Human Beings: There Is Life beyond Security , 2012, Cognitive Computation.

[17]  Y. Grodzinsky The neurology of syntax: Language use without Broca's area , 2000, Behavioral and Brain Sciences.

[18]  Milan Gnjatović,et al.  Toward computational modeling of the comprehension deficit in Broca ’ s aphasia , 2012 .

[19]  Emilia I. Barakova,et al.  Robots for social training of autistic children : empowering the therapists in intensive training programs , 2011 .

[20]  Marcos Faúndez-Zanuy,et al.  On Automatic Diagnosis of Alzheimer’s Disease Based on Spontaneous Speech Analysis and Emotional Temperature , 2013, Cognitive Computation.

[21]  Vlado Delic,et al.  A cognitively-inspired method for meaning representation in dialogue systems , 2012, 2012 IEEE 3rd International Conference on Cognitive Infocommunications (CogInfoCom).

[22]  Kara D. Federmeier,et al.  Electrophysiology reveals semantic memory use in language comprehension , 2000, Trends in Cognitive Sciences.

[23]  Vlado Delic,et al.  Adaptive multimodal interaction with industrial robot , 2012, 2012 IEEE 10th Jubilee International Symposium on Intelligent Systems and Informatics.

[24]  A. Caramazza,et al.  Dissociation of algorithmic and heuristic processes in language comprehension: Evidence from aphasia , 1976, Brain and Language.

[25]  Hartmut Fitz,et al.  Getting real about Semantic Illusions: Rethinking the functional role of the P600 in language comprehension , 2012, Brain Research.

[26]  D. Lefeber,et al.  Using the social robot probo as a social story telling agent for children with ASD , 2012 .

[27]  Emilia I. Barakova,et al.  Robots for social training of autistic children , 2011, 2011 World Congress on Information and Communication Technologies.

[28]  Tom Ziemke,et al.  Robot-assisted therapy for autism spectrum disorders with (partially) autonomous control: Challenges and outlook , 2012, Paladyn J. Behav. Robotics.

[29]  H. Krebs,et al.  Robot‐assisted task‐specific training in cerebral palsy , 2009, Developmental medicine and child neurology.

[30]  N. Hogan,et al.  Learning, Not Adaptation, Characterizes Stroke Motor Recovery: Evidence From Kinematic Changes Induced by Robot-Assisted Therapy in Trained and Untrained Task in the Same Workspace , 2012, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[31]  M. Covington,et al.  HOW COMPLEX IS THAT SENTENCE? A PROPOSED REVISION OF THE ROSENBERG AND ABBEDUTO D-LEVEL SCALE , 2006 .

[32]  Vlado Delic,et al.  Electrophysiologically-inspired evaluation of dialogue act complexity , 2013, 2013 IEEE 4th International Conference on Cognitive Infocommunications (CogInfoCom).

[33]  Luis A. Hernández Gómez,et al.  Improving Automatic Detection of Obstructive Sleep Apnea Through Nonlinear Analysis of Sustained Speech , 2013, Cognitive Computation.

[34]  Michael A. Goodrich,et al.  Toward Therapist-in-the-Loop Assistive Robotics for Children with Autism and Specific Language Impairment , 2009 .

[35]  M. Blázquez,et al.  Clinical Application of Robotics in Children with Cerebral Palsy , 2013 .

[36]  B. Dan,et al.  A report: the definition and classification of cerebral palsy April 2006 , 2007, Developmental medicine and child neurology. Supplement.

[37]  E. Cabanis,et al.  Paul Broca's historic cases: high resolution MR imaging of the brains of Leborgne and Lelong. , 2007, Brain : a journal of neurology.

[38]  Sidney S. Fels,et al.  Therapist-centred design of NUI based therapies in a neurological care hospital , 2012, 2012 IEEE International Conference on Systems, Man, and Cybernetics (SMC).

[39]  H. Krebs,et al.  Effects of Robot-Assisted Therapy on Upper Limb Recovery After Stroke: A Systematic Review , 2008, Neurorehabilitation and neural repair.

[40]  Jochen Kaiser,et al.  Basic operations in working memory: Contributions from functional imaging studies , 2010, Behavioural Brain Research.

[41]  K. Oberauer Access to information in working memory: exploring the focus of attention. , 2002, Journal of experimental psychology. Learning, memory, and cognition.