Publication statistics

Pub. period:1997-2012
Pub. count:45
Number of co-authors:62



Co-authors

Number of publications with 3 favourite co-authors:

Jennifer Healey:3
Rui Prada:3
Cynthia Breazeal:3

 

 

Productive colleagues

Rosalind W. Picard's 3 most productive colleagues in number of publications:

Henry Lieberman:64
Steve Mann:53
Ana Paiva:52
 
 
 

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Rosalind W. Picard

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web.media.mit.edu/~picard/index.php

Professor Rosalind W. Picard, Sc.D. is founder and director of the Affective Computing Research Group at the Massachusetts Institute of Technology (MIT) Media Laboratory, co-director of the Things That Think Consortium, the largest industrial sponsorship organization at the lab, and leader of the new and growing Autism & Communication Technology Initiative at MIT. She is co-founder, chief scientist and chairman of Affectiva, Inc., making technology to help measure and communicate emotion.

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Publications by Rosalind W. Picard (bibliography)

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2012

Picard, Rosalind W. (2012). Commentary on 'Affective Computing' by Kristina Hook

 
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Sano, Akane, Hernandez, Javier, Deprey, Jean, Eckhardt, Micah, Goodwin, Matthew S. and Picard, Rosalind W. (2012): Multimodal annotation tool for challenging behaviors in people with Autism spectrum disorders. In: Proceedings of the 2012 International Conference on Uniquitous Computing 2012. pp. 737-740.

Individuals diagnosed with Autism Spectrum Disorders (ASD) often have challenging behaviors (CB's), such as self-injury or emotional outbursts, which can negatively impact the quality of life of themselves and those around them. Recent advances in mobile and ubiquitous technologies provide an opportunity to efficiently and accurately capture important information preceding and associated with these CB's. The ability to obtain this type of data will help with both intervention and behavioral phenotyping efforts. Through collaboration with behavioral scientists and therapists, we identified relevant design requirements and created an easy-to-use mobile application for collecting, labeling, and sharing in-situ behavior data in individuals diagnosed with ASD. Furthermore, we have released the application to the community as an open-source project so it can be validated and extended by other researchers.

© All rights reserved Sano et al. and/or ACM Press

 
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Hernandez, Javier, Hoque, Mohammed (Ehsan), Drevo, Will and Picard, Rosalind W. (2012): Mood meter: counting smiles in the wild. In: Proceedings of the 2012 International Conference on Uniquitous Computing 2012. pp. 301-310.

In this study, we created and evaluated a computer vision based system that automatically encouraged, recognized and counted smiles on a college campus. During a ten-week installation, passersby were able to interact with the system at four public locations. The aggregated data was displayed in real time in various intuitive and interactive formats on a public website. We found privacy to be one of the main design constraints, and transparency to be the best strategy to gain participants' acceptance. In a survey (with 300 responses), participants reported that the system made them smile more than they expected, and it made them and others around them feel momentarily better. Quantitative analysis of the interactions revealed periodic patterns (e.g., more smiles during the weekends) and strong correlation with campus events (e.g., fewer smiles during exams, most smiles the day after graduation), reflecting the emotional responses of a large community.

© All rights reserved Hernandez et al. and/or ACM Press

2010
 
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Morris, Robert R., Kirschbaum, Connor R. and Picard, Rosalind W. (2010): Broadening accessibility through special interests: a new approach for software customization. In: Twelfth Annual ACM SIGACCESS Conference on Assistive Technologies 2010. pp. 171-178.

Individuals diagnosed with autism spectrum disorder (ASD) often fixate on narrow, restricted interests. These interests can be highly motivating, but they can also create attentional myopia, preventing individuals from pursuing a broad range of activities. Interestingly, researchers have found that preferred interests can be used to help individuals with ASD branch out and participate in educational, therapeutic, or social situations they might otherwise shun. When interventions are modified, such that an individual's interest is properly represented, task adherence and performance can increase. While this strategy has seen success in the research literature, it is difficult to implement on a large scale and therefore has not been widely adopted. This paper describes a software approach designed to solve this problem. The approach facilitates customization, allowing users to easily embed images of almost any special interest into computer-based interventions. Specifically, we describe an algorithm that will: (1) retrieve any image from the Google image database; (2) strip it of its background; and (3) embed it seamlessly into Flash-based computer programs. To evaluate our algorithm, we employed it in a naturalistic setting with eleven individuals (nine diagnosed with ASD and two diagnosed with other developmental disorders). We also tested its ability to retrieve and process examples of preferred interests previously reported in the ASD literature. The results indicate that our method was an easy and efficient way for users to customize our software programs. While we believe this model is uniquely suited for individuals with ASD, we also foresee this approach being useful for anyone that might like a quick and simple way to personalize software programs.

© All rights reserved Morris et al. and/or their publisher

2009
 
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Madsen, Miriam, Kaliouby, Rana El, Eckhardt, Micah, Hoque, Mohammed E., Goodwin, Matthew S. and Picard, Rosalind W. (2009): Lessons from participatory design with adolescents on the autism spectrum. In: Proceedings of ACM CHI 2009 Conference on Human Factors in Computing Systems 2009. pp. 3835-3840.

Participatory user interface design with adolescent users on the autism spectrum presents a number of unique challenges and opportunities. Through our work developing a system to help autistic adolescents learn to recognize facial expressions, we have learned valuable lessons about software and hardware design issues for this population. These lessons may also be helpful in assimilating iterative user input to customize technology for other populations with special needs.

© All rights reserved Madsen et al. and/or ACM Press

 
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Picard, Rosalind W. (2009): Robots with emotional intelligence. In: Proceedings of the 4th ACM/IEEE International Conference on Human Robot Interaction 2009. pp. 5-6.

This keynote talk will illustrate a basic set of skills of emotional intelligence, how they are important for robots and agents that interact with people, and how our research at MIT addresses part of the problem of giving robots such skills. One of the most important skills is the ability to perceive and understand expressions of emotion, which I will highlight by demonstrating our latest technologies developed to read joint facial-head movements in real-time and associate these with complex affective-cognitive states, and technologies to read paralinguistic vocal cues from speech. The latter have been made open-source and are available for free. I will also show some non-traditional ways robots might sense and learn about human emotion, and ways they can respond to what they sense that can help or hurt people. I will discuss social and ethical issues these technologies raise. Finally, I will present some new possibilities for robots to both learn from people and help teach skills of emotional intelligence to people, especially to those with nonverbal learning impairments who may want to learn these skills, including many people with diagnoses of autism spectrum disorders such as Aspergers Syndrome.

© All rights reserved Picard and/or ACM Press

2008
 
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Kim, Kyunghee, Picard, Rosalind W. and Lieberman, Henry (2008): Common sense assistant for writing stories that teach social skills. In: Proceedings of ACM CHI 2008 Conference on Human Factors in Computing Systems April 5-10, 2008. pp. 2805-2810.

People on the autistic spectrum often have difficulties with social interaction, and these difficulties are compounded when a person faces the uncertainty of not knowing what to expect in a new social setting. Detailed, step-by-step explanations of people's intentions and plausible actions can often help autistic people make sense of the situation, adapt to the social rules, and reduce stress associated with the social encounter. Carol Gray's Social Stories? are carefully structured stories designed to prepare autistic people for everyday situations such as smiling at friends, waiting in a line, and staying calm in an audience when the speaker's slides don't match the handouts. Teachers or parents writing these stories often forget to include explanations of simple, "common sense" facts and simple variations of the story that might occur in different circumstances. We present a new tool that helps the writer explain salient points and think of more variations of the story. It uses a knowledge base of Common Sense sentences, Open Mind Common Sense, and inference in a semantic network, ConceptNet. We are investigating whether this new tool's suggestions are useful by examining how often the writers choose and use the suggestions that it generates.

© All rights reserved Kim et al. and/or ACM Press

 
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Lee, Chia-Hsun Jackie, Morris, Rob, Goodwin, Matthew and Picard, Rosalind W. (2008): Lessons learned from a pilot study quantifying face contact and skin conductance in teens with asperger syndrome. In: Proceedings of ACM CHI 2008 Conference on Human Factors in Computing Systems April 5-10, 2008. pp. 3147-3152.

This paper presents lessons learned from a preliminary study quantifying face contact and corresponding physiological reactivity in teenagers with Asperger syndrome. In order to detect face contact and physiological arousability, we created a wearable system that combines a camera with OpenCV face detection and skin conductance sensors. In this paper, we discuss issues involved in setting up experimental environments for wearable platforms to detect face contact and skin conductance levels simultaneously, and address technological, statistical, and ethical considerations for future technological interventions.

© All rights reserved Lee et al. and/or ACM Press

 
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Lee, Chia-Hsun Jackie, Kim, Kyunghee, Breazeal, Cynthia and Picard, Rosalind W. (2008): Shybot: friend-stranger interaction for children living with autism. In: Proceedings of ACM CHI 2008 Conference on Human Factors in Computing Systems April 5-10, 2008. pp. 3375-3380.

This paper presents Shybot, a personal mobile robot designed to both embody and elicit reflection on shyness behaviors. Shybot is being designed to detect human presence and familiarity from face detection and proximity sensing in order to categorize people as friends or strangers to interact with. Shybot also can reflect elements of the anxious state of its human companion through LEDs and a spinning propeller. We designed this simple social interaction to open up a new direction for intervention for children living with autism. We hope that from minimal social interaction, a child with autism or social anxiety disorders could reflect on and more deeply attain understanding about personal shyness behaviors, as a first step toward helping make progress in developing greater capacity for complex social interaction.

© All rights reserved Lee et al. and/or ACM Press

 
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Madsen, Miriam, Kaliouby, Rana El, Goodwin, Matthew and Picard, Rosalind W. (2008): Technology for just-in-time in-situ learning of facial affect for persons diagnosed with an autism spectrum disorder. In: Tenth Annual ACM SIGACCESS Conference on Assistive Technologies 2008. pp. 19-26.

Many first-hand accounts from individuals diagnosed with autism spectrum disorders (ASD) highlight the challenges inherent in processing high-speed, complex, and unpredictable social information such as facial expressions in real-time. In this paper, we describe a new technology aimed at helping people capture, analyze, and reflect on a set of social-emotional signals communicated by facial and head movements in live social interaction that occurs with their everyday social companions. We describe our development of a new combination of hardware using a miniature camera connected to an ultramobile PC together with custom software developed to track, capture, interpret, and intuitively present various interpretations of the facial-head movements (e.g., presenting that there is a high probability the person looks "confused"). This paper describes this new technology together with the results of a series of pilot studies conducted with adolescents diagnosed with ASD who used the technology in their peer-group setting and contributed to its development via their feedback.

© All rights reserved Madsen et al. and/or ACM Press

2007
 
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Ana, Paiva,, Prada, Rui and Picard, Rosalind W. (2007): Affective Computing and Intelligent Interaction, Lecture Notes in Computer Science, Vol. 4738. Berlin, Germany, Springer Verlag

 
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Kapoor, Ashish, Burleson, Winslow and Picard, Rosalind W. (2007): Automatic prediction of frustration. In International Journal of Human-Computer Studies, 65 (8) pp. 724-736.

Predicting when a person might be frustrated can provide an intelligent system with important information about when to initiate interaction. For example, an automated Learning Companion or Intelligent Tutoring System might use this information to intervene, providing support to the learner who is likely to otherwise quit, while leaving engaged learners free to discover things without interruption. This paper presents the first automated method that assesses, using multiple channels of affect-related information, whether a learner is about to click on a button saying "I'm frustrated." The new method was tested on data gathered from 24 participants using an automated Learning Companion. Their indication of frustration was automatically predicted from the collected data with 79% accuracy (chance=58%). The new assessment method is based on Gaussian process classification and Bayesian inference. Its performance suggests that non-verbal channels carrying affective cues can help provide important information to a system for formulating a more intelligent response.

© All rights reserved Kapoor et al. and/or Academic Press

 Cited in the following chapter:

Multimodal Affective Computing: [/encyclopedia/multimodal_affective_computing.html]


 
 
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Picard, Rosalind W. and Liu, Karen K. (2007): Relative subjective count and assessment of interruptive technologies applied to mobile monitoring of stress. In International Journal of Human-Computer Studies, 65 (4) pp. 361-375.

A variety of technologies -- from agents designed to assist or encourage you, to context-based messaging services -- have the opportunity to interrupt you many times throughout the day. One of the challenges with designing new highly interruptive technologies is how to objectively assess their influence on human experience. This paper presents an assessment of a new mobile system that interrupts the wearer to support self-monitoring of stress. We utilize a diverse set of assessment techniques, including a newly proposed measure, relative subjective count, which compares the difference in perceived number of interruptions to actual number of interruptions. This measure, together with direct and indirect subjective reports, and a behavioral choice, is used to evaluate an empathetic version of the mobile system vs. a non-empathetic version. We found that post-experience direct questionnaire assessments such as "how stressful has using the system been?" do not significantly distinguish user experiences with the two systems; however, the new measure of relative subjective count, the behavioral choice, and another indirect questioning strategy, do point toward a preference for the empathetic system.

© All rights reserved Picard and Liu and/or Academic Press

 
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Paiva, Ana, Prada, Rui and Picard, Rosalind W. (eds.) Proceedings of the Second International Conference on Affective Computing and Intelligent Interaction September 12-14, 2007, Lisbon, Portugal.

 
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Breazeal, Cynthia, Wang, Andrew and Picard, Rosalind W. (2007): Experiments with a robotic computer: body, affect and cognition interactions. In: Proceedings of the ACM/IEEE International Conference on Human-Robot Interaction 2007. pp. 153-160.

We present RoCo, the first robotic computer designed with the ability to move its monitor in subtly expressive ways that respond to and encourage its user's own postural movement. We use RoCo in a novel user study to explore whether a computer's "posture" can influence its user's subsequent posture, and if the interaction of the user's body state with their affective state during a task leads to improved task measures such as persistence in problem solving. We believe this is possible in light of new theories that link physical posture and its influence on affect and cognition. Initial results with 71 subjects support the hypothesis that RoCo's posture not only manipulates the user's posture, but also is associated with hypothesized posture-affect interactions. Specifically, we found effects on increased persistence on a subsequent cognitive task, and effects on perceived level of comfort.

© All rights reserved Breazeal et al. and/or ACM Press

 
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Paiva, Ana, Prada, Rui and Picard, Rosalind W. (eds.) ACII 2007 - Affective Computing and Intelligent Interaction, Second International Conference September 12-14, 2007, Lisbon, Portugal.

 
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Ahn, Hyungil, Teeters, Alea, Wang, Andrew, Breazeal, Cynthia and Picard, Rosalind W. (2007): Stoop to Conquer: Posture and Affect Interact to Influence Computer Users' Persistence. In: Paiva, Ana, Prada, Rui and Picard, Rosalind W. (eds.) ACII 2007 - Affective Computing and Intelligent Interaction, Second International Conference September 12-14, 2007, Lisbon, Portugal. pp. 582-593.

2006
 
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Larson, K., Hazlett, R. L., Chaparro, B. S. and Picard, Rosalind W. (2006): Measuring the Aesthetics of Reading. In: Proceedings of the HCI06 Conference on People and Computers XX 2006. pp. 41-56.

2005
 
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Tao, Jianhua, Tan, Tieniu and Picard, Rosalind W. (eds.) Proceedings of the 1st International Conference on Affective Computing and Intelligent Interaction 22-24 October, 2005, Beijing, China.

 
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Kapoor, Ashish and Picard, Rosalind W. (2005): Multimodal affect recognition in learning environments. In: Zhang, Hongjiang, Chua, Tat-Seng, Steinmetz, Ralf, Kankanhalli, Mohan S. and Wilcox, Lynn (eds.) Proceedings of the 13th ACM International Conference on Multimedia November 6-11, 2005, Singapore. pp. 677-682.

 
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Tao, Jianhua, Tan, Tieniu and Picard, Rosalind W. (eds.) ACII 2005 - Affective Computing and Intelligent Interaction, First International Conference October 22-24, 2005, Beijing, China.

 
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Ahn, Hyungil and Picard, Rosalind W. (2005): Affective-Cognitive Learning and Decision Making: A Motivational Reward Framework for Affective Agents. In: Tao, Jianhua, Tan, Tieniu and Picard, Rosalind W. (eds.) ACII 2005 - Affective Computing and Intelligent Interaction, First International Conference October 22-24, 2005, Beijing, China. pp. 866-873.

 
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Strauss, Marc, Reynolds, Carson, Hughes, Stephen, Park, Kyoung, McDarby, Gary and Picard, Rosalind W. (2005): The HandWave Bluetooth Skin Conductance Sensor. In: Tao, Jianhua, Tan, Tieniu and Picard, Rosalind W. (eds.) ACII 2005 - Affective Computing and Intelligent Interaction, First International Conference October 22-24, 2005, Beijing, China. pp. 699-706.

 
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Picard, Rosalind W. (2005): Emotional Intelligence in Agents and Interactive Computers. In: Chen, Chin-Sheng, Filipe, Joaquim, Seruca, Isabel and Cordeiro, Jos (eds.) ICEIS 2005 - Proceedings of the Seventh International Conference on Enterprise Information Systems May 25-28, 2005, Miami, USA. pp. 9-10.

2003
 
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Mueller, Florian, Agamanolis, Stefan and Picard, Rosalind W. (2003): Exertion interfaces: sports over a distance for social bonding and fun. In: Cockton, Gilbert and Korhonen, Panu (eds.) Proceedings of the ACM CHI 2003 Human Factors in Computing Systems Conference April 5-10, 2003, Ft. Lauderdale, Florida, USA. pp. 561-568.

 
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Picard, Rosalind W. (2003): Affective computing: challenges. In International Journal of Human-Computer Studies, 59 (1) pp. 55-64.

A number of researchers around the world have built machines that recognize, express, model, communicate, and respond to emotional information, instances of "affective computing." This article raises and responds to several criticisms of affective computing, articulating state-of-the art research challenges, especially with respect to affect in human-computer interaction.

© All rights reserved Picard and/or Academic Press

 
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Picard, Rosalind W. (2003): Affective computing: challenges. In International Journal of Human-Computer Studies, 1 pp. 55-64.

 Cited in the following chapter:

Multimodal Affective Computing: [/encyclopedia/multimodal_affective_computing.html]


 
 
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Picard, Rosalind W. (2003): Computers That Recognize and Respond to User Emotion. In: Brusilovsky, Peter, Corbett, Albert T. and Rosis, Fiorella De (eds.) User Modeling 2003 - 9th International Conference - UM 2003 June 22-26, 2003, Johnstown, PA, USA. p. 2.

2002
 
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Scheirer, Jocelyn, Fernandez, Raul, Klein, Jonathan and Picard, Rosalind W. (2002): Frustrating the user on purpose: a step toward building an affective computer. In Interacting with Computers, 14 (2) pp. 93-118.

Using a deliberately slow computer-game-interface to induce a state of hypothesised frustration in users, we collected physiological, video and behavioural data, and developed a strategy for coupling these data with real-world events. The effectiveness of our strategy was tested in a study with thirty six subjects, where the system was shown to reliably synchronise and gather data for affect analysis. A pattern-recognition strategy known as Hidden Markov Models was applied to each subject's physiological signals of skin conductivity and blood volume pressure in an effort to see if regimes of likely frustration could be automatically discriminated from regimes when frustration was much less likely. This pattern-recognition approach performed significantly better than random guessing at classifying the two regimes. Mouse-clicking behaviour was also synchronised to frustration-eliciting events and analysed, revealing four distinct patterns of clicking responses. We provide recommendations and guidelines for using physiology as a dependent measure for HCI experiments, especially when considering human emotions in the HCI equation.

© All rights reserved Scheirer et al. and/or Elsevier Science

 
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Klein, J., Moon, Youngme and Picard, Rosalind W. (2002): This computer responds to user frustration:: Theory, design, and results. In Interacting with Computers, 14 (2) pp. 119-140.

Use of technology often has unpleasant side effects, which may include strong, negative emotional states that arise during interaction with computers. Frustration, confusion, anger, anxiety and similar emotional states can affect not only the interaction itself, but also productivity, learning, social relationships, and overall well-being. This paper suggests a new solution to this problem: designing human-computer interaction systems to actively support users in their ability to manage and recover from negative emotional states. An interactive affect-support agent was designed and built to test the proposed solution in a situation where users were feeling frustration. The agent, which used only text and buttons in a graphical user interface for its interaction, demonstrated components of active listening, empathy, and sympathy in an effort to support users in their ability to recover from frustration. The agent's effectiveness was evaluated against two control conditions, which were also text-based interactions: (1) users' emotions were ignored, and (2) users were able to report problems and 'vent' their feelings and concerns to the computer. Behavioral results showed that users chose to continue to interact with the system that had caused their frustration significantly longer after interacting with the affect-support agent, in comparison with the two controls. These results support the prediction that the computer can undo some of the negative feelings it causes by helping a user manage his or her emotional state.

© All rights reserved Klein et al. and/or Elsevier Science

 
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Picard, Rosalind W. and Klein, Jonathan (2002): Computers that recognise and respond to user emotion: theoretical and practical implications. In Interacting with Computers, 14 (2) pp. 141-169.

Prototypes of interactive computer systems have been built that can begin to detect and label aspects of human emotional expression, and that respond to users experiencing frustration and other negative emotions with emotionally supportive interactions, demonstrating components of human skills such as active listening, empathy, and sympathy. These working systems support the prediction that a computer can begin to undo some of the negative feelings it causes by helping a user manage his or her emotional state. This paper clarifies the philosophy of this new approach to human-computer interaction: deliberately recognising and responding to an individual user's emotions in ways, that help users meet their needs. We define user needs in a broader perspective than has been hitherto discussed in the HCI community, to include emotional and social needs, and examine technology's emerging capability to address and support such needs. We raise and discuss potential concerns and objections regarding this technology, and describe several opportunities for future work.

© All rights reserved Picard and Klein and/or Elsevier Science

 
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Aist, Gregory, Kort, Barry, Reilly, Rob, Mostow, Jack and Picard, Rosalind W. (2002): Experimentally Augmenting an Intelligent Tutoring System with Human-Supplied Capabilities: Adding Human-Provided Emotional Scaffolding to an Automated Reading Tutor that Listens. In: 4th IEEE International Conference on Multimodal Interfaces - ICMI 2002 14-16 October, 2002, Pittsburgh, PA, USA. pp. 483-490.

 
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Aist, Gregory, Kort, Barry, Reilly, Rob, Mostow, Jack and Picard, Rosalind W. (2002): Experimentally Augmenting an Intelligent Tutoring System with Human-Supplied Capabilities: Adding Human-Provided Emotional Scaffolding to an Automated Reading Tutor that Listens. In: Proceedings of the 2002 International Conference on Multimodal Interfaces 2002. p. 483.

This paper presents the first statistically reliable empirical evidence from a controlled study for the effect of human-provided emotional scaffolding on student persistence in an intelligent tutoring system. We describe an experiment that added human-provided emotional scaffolding to an automated Reading Tutor that listens, and discuss the methodology we developed to conduct this experiment. Each student participated in one (experimental) session with emotional scaffolding, and in one (control) session without emotional scaffolding, counterbalanced by order of session. Each session was divided into several portions. After each portion of the session was completed, the Reading Tutor gave the student a choice: continue, or quit. We measured persistence as the number of portions the student completed. Human-provided emotional scaffolding added to the automated Reading Tutor resulted in increased student persistence, compared to the Reading Tutor alone. Increased persistence means increased time on task, which ought lead to improved learning. If these results for reading turn out to hold for other domains too, the implication for intelligent tutoring systems is that they should respond with not just cognitive support -- but emotional scaffolding as well. Furthermore, the general technique of adding human-supplied capabilities to an existing intelligent tutoring system should prove useful for studying other ITSs too. This paper is a shortened and revised version of Aist et al. (same title). ITS Workshop on Empirical Methods for Tutorial Dialogue. June 4, 2002, San Sebastian, Spain.

© All rights reserved Aist et al. and/or their publisher

2001
 
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Reynolds, C. and Picard, Rosalind W. (2001): Designing for Affective Interactions. In: Proceedings of the Ninth International Conference on Human-Computer Interaction 2001. pp. 499-503.

 
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Picard, Rosalind W. and Scheirer, J. C. (2001): The Galvactivator: A Glove that Senses and Communicates Skin Conductivity. In: Proceedings of the Ninth International Conference on Human-Computer Interaction 2001. pp. 1538-1542.

 
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Picard, Rosalind W., Vyzas, Elias and Healey, Jennifer (2001): Toward machine emotional intelligence: analysis of affective physiological state. In IEEE Transactions on Pattern Analysis and Machine Intelligence, 23 (10) pp. 1175-1191.

 Cited in the following chapter:

Multimodal Affective Computing: [/encyclopedia/multimodal_affective_computing.html]


 
 
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Kort, Barry, Reilly, Rob and Picard, Rosalind W. (2001): An Affective Model of Interplay between Emotions and Learning: Reengineering Educational Pedagogy - Building a Learning Companion. In: ICALT 2001 2001. pp. 43-48.

 Cited in the following chapter:

Affective Computing: [/encyclopedia/affective_computing.html]


 
2000
 
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Picard, Rosalind W. (2000): Affective Perception. In Communications of the ACM, 43 (3) pp. 50-51.

 
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Picard, Rosalind W. (2000): Synthetic Emotion. In IEEE Computer Graphics and Applications, 20 (1) pp. 52-53.

 
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Picard, Rosalind W. (2000): Affective Computing. The MIT Press

The latest scientific findings indicate that emotions play an essential role in decision making, perception, learning, and more -- that is, they influence the very mechanisms of rational thinking. Not only too much, but too little emotion can impair decision making. According to Rosalind Picard, if we want computers to be genuinely intelligent and to interact naturally with us, we must give computers the ability to recognize, understand, even to have and express emotions.Part 1 of this book provides the intellectual framework for affective computing. It includes background on human emotions, requirements for emotionally intelligent computers, applications of affective computing, and moral and social questions raised by the technology. Part 2 discusses the design and construction of affective computers. Although this material is more technical than that in Part 1, the author has kept it less technical than typical scientific publications in order to make it accessible to newcomers. Topics in Part 2 include signal-based representations of emotions, human affect recognition as a pattern recognition and learning problem, recent and ongoing efforts to build models of emotion for synthesizing emotions in computers, and the new application area of affective wearable computers.

© All rights reserved Picard and/or The MIT Press

1999
 
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Picard, Rosalind W. (1999): Affective Computing for HCI. In: Bullinger, Hans-Jrg (ed.) HCI International 1999 - Proceedings of the 8th International Conference on Human-Computer Interaction August 22-26, 1999, Munich, Germany. pp. 829-833.

1998
 
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Hayes-Roth, Barbara, Ball, Gene, Lisetti, Christine, Picard, Rosalind W. and Stern, Andrew (1998): Affect and Emotion in the User Interface. In: Marks, Joe (ed.) International Conference on Intelligent User Interfaces 1998 January 6-9, 1998, San Francisco, California, USA. pp. 91-94.

Intelligence. So much of our technology revolves around intelligence: technology in support of intellectual activities; the goal of engineering artificial intelligence; the need for intelligence in the user interface. And yet, so much of everyday life is really about affect and emotion: differences in performance under conditions that are supportive, threatening, or punishing; the challenges of conflict resolution and cooperation among heterogeneous groups of people; the implicit messages of body language and conversational style; the spirit-sustaining texture of our affective relationships with family and friends.

© All rights reserved Hayes-Roth et al. and/or ACM Press

1997
 
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Picard, Rosalind W. (1997): Affective computing. Ma, USA, The MIT Press

 Cited in the following chapters:

Multimodal Affective Computing: [/encyclopedia/multimodal_affective_computing.html]

Affective Computing: [/encyclopedia/affective_computing.html]


 
 
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Picard, Rosalind W. and Healey, Jennifer (1997): Affective Wearables. In Personal and Ubiquitous Computing, 1 (3) .

 
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Starner, Thad, Mann, Steve, Rhodes, Bradley J., Levine, Jeffrey, Healey, Jennifer, Kirsch, Dana, Picard, Rosalind W. and Pentland, Alex (1997): Augmented Reality Through Wearable Computing. In Presence: Teleoperators and Virtual Environments, 6 (4) pp. 386-398.

 
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Page Information

Page maintainer: The Editorial Team
URL: http://www.interaction-design.org/references/authors/rosalind_w__picard.html

Publication statistics

Pub. period:1997-2012
Pub. count:45
Number of co-authors:62



Co-authors

Number of publications with 3 favourite co-authors:

Jennifer Healey:3
Rui Prada:3
Cynthia Breazeal:3

 

 

Productive colleagues

Rosalind W. Picard's 3 most productive colleagues in number of publications:

Henry Lieberman:64
Steve Mann:53
Ana Paiva:52
 
 
 

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