Publications
Search
501.
Jones, Andrew; Unger, Jonas; Nagano, Koki; Busch, Jay; Yu, Xueming; Peng, Hsuan-Yueh; Alexander, Oleg; Debevec, Paul
Building a Life-Size Automultiscopic Display Using Consumer Hardware Proceedings Article
In: Proceedings of GPU Technology Conference, San Jose, CA, 2015.
@inproceedings{jones_building_2015,
title = {Building a Life-Size Automultiscopic Display Using Consumer Hardware},
author = {Andrew Jones and Jonas Unger and Koki Nagano and Jay Busch and Xueming Yu and Hsuan-Yueh Peng and Oleg Alexander and Paul Debevec},
url = {http://ict.usc.edu/pubs/Building%20a%20Life-Size%20Automultiscopic%20Display%20Using%20Consumer%20Hardware.pdf},
year = {2015},
date = {2015-03-01},
booktitle = {Proceedings of GPU Technology Conference},
address = {San Jose, CA},
abstract = {Automultiscopic displays allow multiple users to experience 3D content without the hassle of special glasses or head gear. Such displays generate many simultaneous images with high-angular density, so that each eye perceives a distinct and different view. This presents a unique challenge for content acquisition and rendering. In this talk, we explain how to build an automultiscopic display using off-the-shelf projectors, video-splitters, and graphics cards. We also present a GPU-based algorithm for rendering a large numbers of views from a sparse array of video cameras.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Automultiscopic displays allow multiple users to experience 3D content without the hassle of special glasses or head gear. Such displays generate many simultaneous images with high-angular density, so that each eye perceives a distinct and different view. This presents a unique challenge for content acquisition and rendering. In this talk, we explain how to build an automultiscopic display using off-the-shelf projectors, video-splitters, and graphics cards. We also present a GPU-based algorithm for rendering a large numbers of views from a sparse array of video cameras.
502.
Ward, Nigel G.; DeVault, David
Ten Challenges in Highly-Interactive Dialog Systems Proceedings Article
In: Proceedings of AAAI 2015 Spring Symposium, Palo Alto, CA, 2015.
@inproceedings{ward_ten_2015,
title = {Ten Challenges in Highly-Interactive Dialog Systems},
author = {Nigel G. Ward and David DeVault},
url = {http://ict.usc.edu/pubs/Ten%20Challenges%20in%20Highly-Interactive%20Dialog%20Systems.pdf},
year = {2015},
date = {2015-03-01},
booktitle = {Proceedings of AAAI 2015 Spring Symposium},
address = {Palo Alto, CA},
abstract = {Systems capable of highly-interactive dialog have recently been developed in several domains. This paper considers how to build on these successes to make systems more robust, easier to develop, more adaptable, and more scientifically significant.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Systems capable of highly-interactive dialog have recently been developed in several domains. This paper considers how to build on these successes to make systems more robust, easier to develop, more adaptable, and more scientifically significant.
503.
DeVault, David; Mell, Jonathan; Gratch, Jonathan
Toward Natural Turn-Taking in a Virtual Human Negotiation Agent Proceedings Article
In: AAAI Spring Symposium on Turn-taking and Coordination in Human-Machine Interaction, pp. 2–9, AAAI Press, Palo Alto, California, 2015.
@inproceedings{devault_toward_2015,
title = {Toward Natural Turn-Taking in a Virtual Human Negotiation Agent},
author = {David DeVault and Jonathan Mell and Jonathan Gratch},
url = {http://ict.usc.edu/pubs/Toward%20Natural%20Turn-Taking%20in%20a%20Virtual%20Human%20Negotiation%20Agent.pdf},
year = {2015},
date = {2015-03-01},
booktitle = {AAAI Spring Symposium on Turn-taking and Coordination in Human-Machine Interaction},
pages = {2–9},
publisher = {AAAI Press},
address = {Palo Alto, California},
abstract = {In this paper we assess our progress toward creating a virtual human negotiation agent with fluid turn-taking skills. To facilitate the design of this agent, we have collected a corpus of human-human negotiation roleplays as well as a corpus of Wizard-controlled human-agent negotiations in the same roleplay scenario.We compare the natural turn-taking behavior in our human-human corpus with that achieved in our Wizard-of-Oz corpus, and quantify our virtual human’s turn-taking skills using a combination of subjective and objective metrics. We also discuss our design for a Wizard user interface to support real-time control of the virtual human’s turntaking and dialogue behavior, and analyze our wizard’s usage of this interface.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
In this paper we assess our progress toward creating a virtual human negotiation agent with fluid turn-taking skills. To facilitate the design of this agent, we have collected a corpus of human-human negotiation roleplays as well as a corpus of Wizard-controlled human-agent negotiations in the same roleplay scenario.We compare the natural turn-taking behavior in our human-human corpus with that achieved in our Wizard-of-Oz corpus, and quantify our virtual human’s turn-taking skills using a combination of subjective and objective metrics. We also discuss our design for a Wizard user interface to support real-time control of the virtual human’s turntaking and dialogue behavior, and analyze our wizard’s usage of this interface.
504.
Casas, Dan; Alexander, Oleg; Feng, Andrew W.; Fyffe, Graham; Ichikari, Ryosuke; Debevec, Paul; Wang, Rhuizhe; Suma, Evan; Shapiro, Ari
Rapid Photorealistic Blendshapes from Commodity RGB-D Sensors Proceedings Article
In: Proceedings of the 19th Symposium on Interactive 3D Graphics and Games, pp. 134–134, ACM Press, San Francisco, CA, 2015, ISBN: 978-1-4503-3392-4.
@inproceedings{casas_rapid_2015,
title = {Rapid Photorealistic Blendshapes from Commodity RGB-D Sensors},
author = {Dan Casas and Oleg Alexander and Andrew W. Feng and Graham Fyffe and Ryosuke Ichikari and Paul Debevec and Rhuizhe Wang and Evan Suma and Ari Shapiro},
url = {http://dl.acm.org/citation.cfm?doid=2699276.2721398},
doi = {10.1145/2699276.2721398},
isbn = {978-1-4503-3392-4},
year = {2015},
date = {2015-02-01},
booktitle = {Proceedings of the 19th Symposium on Interactive 3D Graphics and Games},
pages = {134–134},
publisher = {ACM Press},
address = {San Francisco, CA},
abstract = {Creating and animating a realistic 3D human face has been an important task in computer graphics. The capability of capturing the 3D face of a human subject and reanimate it quickly will find many applications in games, training simulations, and interactive 3D graphics. In this paper, we propose a system to capture photorealistic 3D faces and generate the blendshape models automatically using only a single commodity RGB-D sensor. Our method can rapidly generate a set of expressive facial poses from a single Microsoft Kinect and requires no artistic expertise on the part of the capture subject. The system takes only a matter of seconds to capture and produce a 3D facial pose and only requires 4 minutes of processing time to transform it into a blendshape model. Our main contributions include an end-to-end pipeline for capturing and generating face blendshape models automatically, and a registration method that solves dense correspondences between two face scans by utilizing facial landmark detection and optical flow. We demonstrate the effectiveness of the proposed method by capturing 3D facial models of different human subjects and puppeteering their models in an animation system with real-time facial performance retargeting.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Creating and animating a realistic 3D human face has been an important task in computer graphics. The capability of capturing the 3D face of a human subject and reanimate it quickly will find many applications in games, training simulations, and interactive 3D graphics. In this paper, we propose a system to capture photorealistic 3D faces and generate the blendshape models automatically using only a single commodity RGB-D sensor. Our method can rapidly generate a set of expressive facial poses from a single Microsoft Kinect and requires no artistic expertise on the part of the capture subject. The system takes only a matter of seconds to capture and produce a 3D facial pose and only requires 4 minutes of processing time to transform it into a blendshape model. Our main contributions include an end-to-end pipeline for capturing and generating face blendshape models automatically, and a registration method that solves dense correspondences between two face scans by utilizing facial landmark detection and optical flow. We demonstrate the effectiveness of the proposed method by capturing 3D facial models of different human subjects and puppeteering their models in an animation system with real-time facial performance retargeting.
505.
Talbot, Thomas
COMRADE: Methods for Adaptive Competency Management and Just-in-Time Clinical Acumen Augmentation Journal Article
In: MedSim Magazine, pp. 26 – 28, 2015.
@article{talbot_comrade_2015,
title = {COMRADE: Methods for Adaptive Competency Management and Just-in-Time Clinical Acumen Augmentation},
author = {Thomas Talbot},
url = {http://ict.usc.edu/pubs/COMRADE%20-%20Methods%20for%20Adaptive%20Competency%20Management%20and%20Just-in-Time%20Clinical%20Acumen%20Augmentation.pdf},
year = {2015},
date = {2015-01-01},
journal = {MedSim Magazine},
pages = {26 – 28},
abstract = {Dr. Thomas Talbot shares ideas for enhancing the electronic medical Record to act as a didactic tool to support physician competency.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Dr. Thomas Talbot shares ideas for enhancing the electronic medical Record to act as a didactic tool to support physician competency.
506.
Corbin, Carina; Morbini, Fabrizio; Traum, David
Creating a Virtual Neighbor Proceedings Article
In: Proceedings of International Workshop on Spoken Dialogue Systems, Busan, South Korea, 2015.
@inproceedings{corbin_creating_2015,
title = {Creating a Virtual Neighbor},
author = {Carina Corbin and Fabrizio Morbini and David Traum},
url = {http://ict.usc.edu/pubs/Creating%20a%20Virtual%20Neighbor.pdf},
year = {2015},
date = {2015-01-01},
booktitle = {Proceedings of International Workshop on Spoken Dialogue Systems},
address = {Busan, South Korea},
abstract = {We present the first version of our Virtual Neighbor, who can talk with users about people employed in the same institution. The Virtual Neighbor can discuss information about employees in a medium sized company or institute with users. The system acquires information from three sources: a personnel directory database, public web pages, and through dialogue interaction. Users can interact through face to face spoken dialogue, using components from the ICT Virtual human toolkit, or via a chat interface.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
We present the first version of our Virtual Neighbor, who can talk with users about people employed in the same institution. The Virtual Neighbor can discuss information about employees in a medium sized company or institute with users. The system acquires information from three sources: a personnel directory database, public web pages, and through dialogue interaction. Users can interact through face to face spoken dialogue, using components from the ICT Virtual human toolkit, or via a chat interface.
507.
Morency, Louis-Philippe; Stratou, Giota; DeVault, David; Hartholt, Arno; Lhommet, Margaux; Lucas, Gale; Morbini, Fabrizio; Georgila, Kallirroi; Scherer, Stefan; Gratch, Jonathan; Marsella, Stacy; Traum, David; Rizzo, Albert "Skip"
SimSensei Demonstration: A Perceptive Virtual Human Interviewer for Healthcare Applications Proceedings Article
In: Proceedings of the 29th AAAI Conference on Artificial Intelligence (AAAI), Austin, Texas, 2015.
@inproceedings{morency_simsensei_2015,
title = {SimSensei Demonstration: A Perceptive Virtual Human Interviewer for Healthcare Applications},
author = {Louis-Philippe Morency and Giota Stratou and David DeVault and Arno Hartholt and Margaux Lhommet and Gale Lucas and Fabrizio Morbini and Kallirroi Georgila and Stefan Scherer and Jonathan Gratch and Stacy Marsella and David Traum and Albert "Skip" Rizzo},
url = {http://ict.usc.edu/pubs/SimSensei%20Demonstration%20A%20Perceptive%20Virtual%20Human%20Interviewer%20for%20Healthcare%20Applications.pdf},
year = {2015},
date = {2015-01-01},
booktitle = {Proceedings of the 29th AAAI Conference on Artificial Intelligence (AAAI)},
address = {Austin, Texas},
abstract = {We present the SimSensei system, a fully automatic virtual agent that conducts interviews to assess indicators of psychological distress. We emphasize on the perception part of the system, a multimodal framework which captures and analyzes user state for both behavioral understanding and interactional purposes.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
We present the SimSensei system, a fully automatic virtual agent that conducts interviews to assess indicators of psychological distress. We emphasize on the perception part of the system, a multimodal framework which captures and analyzes user state for both behavioral understanding and interactional purposes.
508.
Rosenbloom, Paul S.; Demski, Abram; Ustun, Volkan
Efficient message computation in Sigma’s graphical architecture Journal Article
In: Biologically Inspired Cognitive Architectures, vol. 11, pp. 1–9, 2015, ISSN: 2212683X.
@article{rosenbloom_efficient_2015,
title = {Efficient message computation in Sigma’s graphical architecture},
author = {Paul S. Rosenbloom and Abram Demski and Volkan Ustun},
url = {http://linkinghub.elsevier.com/retrieve/pii/S2212683X14000723},
doi = {10.1016/j.bica.2014.11.009},
issn = {2212683X},
year = {2015},
date = {2015-01-01},
journal = {Biologically Inspired Cognitive Architectures},
volume = {11},
pages = {1–9},
abstract = {Human cognition runs at ∼50 ms per cognitive cycle, implying that any biologically inspired cognitive architecture that strives for real-time performance needs to be able to run at this speed. Sigma is a cognitive architecture built upon graphical models – a broadly applicable state-of-the-art formalism for implementing cognitive capabilities – that are solved via message passing (with complex messages based on n-dimensional piecewise-linear functions). Earlier work explored optimizations to Sigma that reduced by an order of magnitude the number of messages sent per cycle. Here, optimizations are introduced that reduce by an order of magnitude the average time required per message sent.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Human cognition runs at ∼50 ms per cognitive cycle, implying that any biologically inspired cognitive architecture that strives for real-time performance needs to be able to run at this speed. Sigma is a cognitive architecture built upon graphical models – a broadly applicable state-of-the-art formalism for implementing cognitive capabilities – that are solved via message passing (with complex messages based on n-dimensional piecewise-linear functions). Earlier work explored optimizations to Sigma that reduced by an order of magnitude the number of messages sent per cycle. Here, optimizations are introduced that reduce by an order of magnitude the average time required per message sent.
509.
Park, Sunghyun; Scherer, Stefan; Gratch, Jonathan; Carnevale, Peter; Morency, Louis-Philippe
I Can Already Guess Your Answer: Predicting Respondent Reactions During Dyadic Negotiation Journal Article
In: IEEE Transactions on Affective Computing, vol. 6, no. 2, pp. 86 –96, 2015, ISSN: 1949-3045.
@article{park_i_2015,
title = {I Can Already Guess Your Answer: Predicting Respondent Reactions During Dyadic Negotiation},
author = {Sunghyun Park and Stefan Scherer and Jonathan Gratch and Peter Carnevale and Louis-Philippe Morency},
url = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=7024926},
doi = {10.1109/TAFFC.2015.2396079},
issn = {1949-3045},
year = {2015},
date = {2015-01-01},
journal = {IEEE Transactions on Affective Computing},
volume = {6},
number = {2},
pages = {86 –96},
abstract = {Negotiation is a component deeply ingrained in our daily lives, and it can be challenging for a person to predict the respondent’s reaction (acceptance or rejection) to a negotiation offer. In this work, we focus on finding acoustic and visual behavioral cues that are predictive of the respondent’s immediate reactions using a face-to-face negotiation dataset, which consists of 42 dyadic interactions in a simulated negotiation setting. We show our results of exploring 4 different sources of information, namely nonverbal behavior of the proposer, that of the respondent, mutual behavior between the interactants related to behavioral symmetry and asymmetry, and past negotiation history between the interactants. Firstly, we show that considering other sources of information (other than the nonverbal behavior of the respondent) can also have comparable performance in predicting respondent reactions. Secondly, we show that automatically extracted mutual behavioral cues of symmetry and asymmetry are predictive partially due to their capturing information of the nature of the interaction itself, whether it is cooperative or competitive. Lastly, we identify audio-visual behavioral cues that are most predictive of the respondent’s immediate reactions.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Negotiation is a component deeply ingrained in our daily lives, and it can be challenging for a person to predict the respondent’s reaction (acceptance or rejection) to a negotiation offer. In this work, we focus on finding acoustic and visual behavioral cues that are predictive of the respondent’s immediate reactions using a face-to-face negotiation dataset, which consists of 42 dyadic interactions in a simulated negotiation setting. We show our results of exploring 4 different sources of information, namely nonverbal behavior of the proposer, that of the respondent, mutual behavior between the interactants related to behavioral symmetry and asymmetry, and past negotiation history between the interactants. Firstly, we show that considering other sources of information (other than the nonverbal behavior of the respondent) can also have comparable performance in predicting respondent reactions. Secondly, we show that automatically extracted mutual behavioral cues of symmetry and asymmetry are predictive partially due to their capturing information of the nature of the interaction itself, whether it is cooperative or competitive. Lastly, we identify audio-visual behavioral cues that are most predictive of the respondent’s immediate reactions.
510.
Marsella, Stacy; Gratch, Jonathan
Computationally Modeling Human Emotion Journal Article
In: Communications of the ACM, vol. 57, no. 12, pp. 56–67, 2014.
@article{marsella_computationally_2014,
title = {Computationally Modeling Human Emotion},
author = {Stacy Marsella and Jonathan Gratch},
url = {http://dl.acm.org/citation.cfm?id=2631912},
doi = {10.1145/2631912},
year = {2014},
date = {2014-12-01},
journal = {Communications of the ACM},
volume = {57},
number = {12},
pages = {56–67},
abstract = {EMOTION’S ROLE IN human behavior is an old debate that has become increasingly relevant to the computational sciences. Two-and-a-half millennia ago, Aristotle espoused a view of emotion at times remarkably similar to modern psychological theories, arguing that emotions (such as anger), in moderation, play a useful role, especially in interactions with others. Those who express anger at appropriate times are praiseworthy, while those lacking in anger at appropriate times are treated as a fool. The Stoics took a different view; four centuries after Aristotle, Seneca considered emotions (such as anger) as a threat to reason, arguing, “reason … is only powerful so long as it remains isolated from emotions.” In the 8th century, David Hume radically departed from the Stoic perspective, arguing for the key motivating role of emotions, saying, “Reason is, and ought only to be the slave of the passions.” A similar dichotomy of views can be seen in the history of artificial intelligence (AI) and agent research.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
EMOTION’S ROLE IN human behavior is an old debate that has become increasingly relevant to the computational sciences. Two-and-a-half millennia ago, Aristotle espoused a view of emotion at times remarkably similar to modern psychological theories, arguing that emotions (such as anger), in moderation, play a useful role, especially in interactions with others. Those who express anger at appropriate times are praiseworthy, while those lacking in anger at appropriate times are treated as a fool. The Stoics took a different view; four centuries after Aristotle, Seneca considered emotions (such as anger) as a threat to reason, arguing, “reason … is only powerful so long as it remains isolated from emotions.” In the 8th century, David Hume radically departed from the Stoic perspective, arguing for the key motivating role of emotions, saying, “Reason is, and ought only to be the slave of the passions.” A similar dichotomy of views can be seen in the history of artificial intelligence (AI) and agent research.
511.
Rizzo, Albert; Scherer, Stefan; DeVault, David; Gratch, Jonathan; Artstein, Ron; Hartholt, Arno; Lucas, Gale; Marsella, Stacy; Morbini, Fabrizio; Nazarian, Angela; Stratou, Giota; Traum, David; Wood, Rachel; Boberg, Jill; Morency, Louis-Philippe
Detection and Computational Analysis of Psychological Signals Using a Virtual Human Interviewing Agent Proceedings Article
In: Proceedings of ICDVRAT 2014, International Journal of Disability and Human Development, Gothenburg, Sweden, 2014.
@inproceedings{rizzo_detection_2014,
title = {Detection and Computational Analysis of Psychological Signals Using a Virtual Human Interviewing Agent},
author = {Albert Rizzo and Stefan Scherer and David DeVault and Jonathan Gratch and Ron Artstein and Arno Hartholt and Gale Lucas and Stacy Marsella and Fabrizio Morbini and Angela Nazarian and Giota Stratou and David Traum and Rachel Wood and Jill Boberg and Louis-Philippe Morency},
url = {http://ict.usc.edu/pubs/Detection%20and%20Computational%20Analysis%20of%20Psychological%20Signals%20Using%20a%20Virtual%20Human%20Interviewing%20Agent.pdf},
year = {2014},
date = {2014-12-01},
booktitle = {Proceedings of ICDVRAT 2014},
publisher = {International Journal of Disability and Human Development},
address = {Gothenburg, Sweden},
abstract = {It has long been recognized that facial expressions, body posture/gestures and vocal parameters play an important role in human communication and the implicit signalling of emotion. Recent advances in low cost computer vision and behavioral sensing technologies can now be applied to the process of making meaningful inferences as to user state when a person interacts with a computational device. Effective use of this additive information could serve to promote human interaction with virtual human (VH) agents that may enhance diagnostic assessment. This paper will focus on our current research in these areas within the DARPA-funded “Detection and Computational Analysis of Psychological Signals” project, with specific attention to the SimSensei application use case. SimSensei is a virtual human interaction platform that is able to sense and interpret real-time audiovisual behavioral signals from users interacting with the system. It is specifically designed for health care support and leverages years of virtual human research and development at USC-ICT. The platform enables an engaging face-to-face interaction where the virtual human automatically reacts to the state and inferred intent of the user through analysis of behavioral signals gleaned from facial expressions, body gestures and vocal parameters. Akin to how non-verbal behavioral signals have an impact on human to human interaction and communication, SimSensei aims to capture and infer from user non-verbal communication to improve engagement between a VH and a user. The system can also quantify and interpret sensed behavioral signals.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
It has long been recognized that facial expressions, body posture/gestures and vocal parameters play an important role in human communication and the implicit signalling of emotion. Recent advances in low cost computer vision and behavioral sensing technologies can now be applied to the process of making meaningful inferences as to user state when a person interacts with a computational device. Effective use of this additive information could serve to promote human interaction with virtual human (VH) agents that may enhance diagnostic assessment. This paper will focus on our current research in these areas within the DARPA-funded “Detection and Computational Analysis of Psychological Signals” project, with specific attention to the SimSensei application use case. SimSensei is a virtual human interaction platform that is able to sense and interpret real-time audiovisual behavioral signals from users interacting with the system. It is specifically designed for health care support and leverages years of virtual human research and development at USC-ICT. The platform enables an engaging face-to-face interaction where the virtual human automatically reacts to the state and inferred intent of the user through analysis of behavioral signals gleaned from facial expressions, body gestures and vocal parameters. Akin to how non-verbal behavioral signals have an impact on human to human interaction and communication, SimSensei aims to capture and infer from user non-verbal communication to improve engagement between a VH and a user. The system can also quantify and interpret sensed behavioral signals.
512.
Andreatta, Pamela; Klotz, Jessica; Madsen, James M.; Hurst, Charles G.; Talbot, Thomas
Assessment instrument validation for critical clinical competencies - pediatricneonatal intubation and cholinergic crisis management Proceedings Article
In: Proceedings of Interservice/Industry Training, Simulation, and Education Conference (I/ITSEC) 2014, Orlando, FL, 2014.
@inproceedings{andreatta_assessment_2014,
title = {Assessment instrument validation for critical clinical competencies - pediatricneonatal intubation and cholinergic crisis management},
author = {Pamela Andreatta and Jessica Klotz and James M. Madsen and Charles G. Hurst and Thomas Talbot},
url = {http://ict.usc.edu/pubs/Assessment%20instrument%20validation%20for%20critical%20clinical%20competencies%20-%20pediatricneonatal%20intubation%20and%20cholinergic%20crisis%20management.pdf},
year = {2014},
date = {2014-12-01},
booktitle = {Proceedings of Interservice/Industry Training, Simulation, and Education Conference (I/ITSEC) 2014},
address = {Orlando, FL},
abstract = {Military and civilian first-responders must be able to recognize and effectively manage casualties that necessitate immediate application of critical clinical competencies. Two examples of these critical competencies are the clinical management of injuries resulting from nerve agents and difficult intubation, especially for pediatric or neonatal patients. The opportunity to learn and practice the necessary skills for these rare, but urgent, situations is complicated by the limited ability to replicate essential situational factors that influence performance in the applied clinical environment. Simulation-based training may resolve some of these challenges, however it is imperative that evidence be captured to document the achievement of performance competencies in the training environment that transfer to applied clinical care. The purpose of this study was to establish psychometric characteristics for competency assessment instruments associated with two such critical competencies: management of cholinergic crisis and pediatric-neonatal intubation. Methods: To inform the development of assessment instruments, we conducted comprehensive task analyses across each performance domain (knowledge, performance). Expert review confirmed content validity. Construct validity was established using the instruments to differentiate between the performance abilities of practitioners with variable experience (novice through expert). Purposively selected firstresponder subjects for pediatric-neonatal intubation (N=214) and cholinergic crisis management (N=123) were stratified by level of experience performing the requisite clinical competencies. All subjects completed knowledge and performance assessments. Reliability was established using test-retest (Pearson correlation) and internal consistency (Cronbach’s alpha) for knowledge and performance assessments. Results: Significantly higher scores for subjects with greater levels of experience, compared to those with less experience established construct validity for each assessment instrument (p textbackslashtextbackslashtextless .01). Significant correlations between test-retest outcomes indicated measurement reliability p textbackslashtextbackslashtextless .01. Cronbach’s alpha for knowledge and performance scores demonstrated excellent internal consistency. Conclusions: Psychometric evidence establishes the value of assessment for identifying and remedying critical competency performance gaps.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Military and civilian first-responders must be able to recognize and effectively manage casualties that necessitate immediate application of critical clinical competencies. Two examples of these critical competencies are the clinical management of injuries resulting from nerve agents and difficult intubation, especially for pediatric or neonatal patients. The opportunity to learn and practice the necessary skills for these rare, but urgent, situations is complicated by the limited ability to replicate essential situational factors that influence performance in the applied clinical environment. Simulation-based training may resolve some of these challenges, however it is imperative that evidence be captured to document the achievement of performance competencies in the training environment that transfer to applied clinical care. The purpose of this study was to establish psychometric characteristics for competency assessment instruments associated with two such critical competencies: management of cholinergic crisis and pediatric-neonatal intubation. Methods: To inform the development of assessment instruments, we conducted comprehensive task analyses across each performance domain (knowledge, performance). Expert review confirmed content validity. Construct validity was established using the instruments to differentiate between the performance abilities of practitioners with variable experience (novice through expert). Purposively selected firstresponder subjects for pediatric-neonatal intubation (N=214) and cholinergic crisis management (N=123) were stratified by level of experience performing the requisite clinical competencies. All subjects completed knowledge and performance assessments. Reliability was established using test-retest (Pearson correlation) and internal consistency (Cronbach’s alpha) for knowledge and performance assessments. Results: Significantly higher scores for subjects with greater levels of experience, compared to those with less experience established construct validity for each assessment instrument (p textbackslashtextbackslashtextless .01). Significant correlations between test-retest outcomes indicated measurement reliability p textbackslashtextbackslashtextless .01. Cronbach’s alpha for knowledge and performance scores demonstrated excellent internal consistency. Conclusions: Psychometric evidence establishes the value of assessment for identifying and remedying critical competency performance gaps.
513.
Klotz, Jessica; Madsen, James M.; Hurst, Charles G.; Talbot, Thomas
Training Effects for First-responder Competency in Cholinergic Crisis Management Proceedings Article
In: Proceedings of Interservice/Industry Training, Simulation, and Education Conference (I/ITSEC) 2014, Orlando, FL, 2014.
@inproceedings{klotz_training_2014,
title = {Training Effects for First-responder Competency in Cholinergic Crisis Management},
author = {Jessica Klotz and James M. Madsen and Charles G. Hurst and Thomas Talbot},
url = {http://ict.usc.edu/pubs/Training%20Effects%20for%20First-responder%20Competency%20in%20Cholinergic%20Crisis%20Management.pdf},
year = {2014},
date = {2014-12-01},
booktitle = {Proceedings of Interservice/Industry Training, Simulation, and Education Conference (I/ITSEC) 2014},
address = {Orlando, FL},
abstract = {Military and civilian first-responders must be able to recognize and effectively manage mass disaster casualties. Clinical management of injuries resulting from nerve agents provides different challenges for first responders than those of conventional weapons. We evaluated the impact of a mixed-methods training program on competency acquisition in cholinergic crisis clinical management. Methods: We developed a multimedia and simulation-based training program based on the more comprehensive USAMRICD courses. The training program was designed to provide first-responders with the necessary abilities to recognize and manage a mass casualty cholinergic crisis event. Training included a learner controlled multimedia iPad app and hands-on instruction using SimMan3G™ mannequin simulators. We evaluated the impact of the training through a purposively selected sample of 204 civilian and military first responders who had not previously completed either of the referenced USAMRICD courses. We assessed knowledge, performance, affect, and self-efficacy measures pre- and post-training using previously validated assessment instruments. We calculated results using analysis of variance with repeated measures, and with statistical significance set at p textbackslashtextbackslashtextless .05. Results: Analyses demonstrated a significant improvement (p = .000) across all domains (knowledge, performance, self-efficacy, and affect). Knowledge scores increased from 60% to 81% correct. Performance scores increased from 16% to 68% correct. Self-efficacy scores increased from 51% to 87% confidence in ability to effectively manage a cholinergic crisis event. Affect scores increased from 75% to 81% personal comfort during procedures. Conclusions: These findings could aid in the selection of instructional methodologies available to a broad community of first-responder personnel in military and civilian service. Although less comprehensive than the USAMRICD courses, training outcomes associated with this easily distributed instruction set demonstrated its value in increasing the competency of first responders in recognizing and managing a mass casualty cholinergic event. Retention outcomes are in process.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Military and civilian first-responders must be able to recognize and effectively manage mass disaster casualties. Clinical management of injuries resulting from nerve agents provides different challenges for first responders than those of conventional weapons. We evaluated the impact of a mixed-methods training program on competency acquisition in cholinergic crisis clinical management. Methods: We developed a multimedia and simulation-based training program based on the more comprehensive USAMRICD courses. The training program was designed to provide first-responders with the necessary abilities to recognize and manage a mass casualty cholinergic crisis event. Training included a learner controlled multimedia iPad app and hands-on instruction using SimMan3G™ mannequin simulators. We evaluated the impact of the training through a purposively selected sample of 204 civilian and military first responders who had not previously completed either of the referenced USAMRICD courses. We assessed knowledge, performance, affect, and self-efficacy measures pre- and post-training using previously validated assessment instruments. We calculated results using analysis of variance with repeated measures, and with statistical significance set at p textbackslashtextbackslashtextless .05. Results: Analyses demonstrated a significant improvement (p = .000) across all domains (knowledge, performance, self-efficacy, and affect). Knowledge scores increased from 60% to 81% correct. Performance scores increased from 16% to 68% correct. Self-efficacy scores increased from 51% to 87% confidence in ability to effectively manage a cholinergic crisis event. Affect scores increased from 75% to 81% personal comfort during procedures. Conclusions: These findings could aid in the selection of instructional methodologies available to a broad community of first-responder personnel in military and civilian service. Although less comprehensive than the USAMRICD courses, training outcomes associated with this easily distributed instruction set demonstrated its value in increasing the competency of first responders in recognizing and managing a mass casualty cholinergic event. Retention outcomes are in process.
514.
Calvo, Rafael A.; D'Mello, Sidney; Gratch, Jonathan; Kappas, Arvid (Ed.)
The Oxford Handbook of Affective Computing Book
Oxford University Press, Oxford ; New York, 2014, ISBN: 978-0-19-994223-7.
@book{calvo_oxford_2014,
title = {The Oxford Handbook of Affective Computing},
editor = {Rafael A. Calvo and Sidney D'Mello and Jonathan Gratch and Arvid Kappas},
url = {https://global.oup.com/academic/product/the-oxford-handbook-of-affective-computing-9780199942237?cc=us&lang=en&},
isbn = {978-0-19-994223-7},
year = {2014},
date = {2014-12-01},
publisher = {Oxford University Press},
address = {Oxford ; New York},
abstract = {The Oxford Handbook of Affective Computing aims to be the definite reference for research in the burgeoning field of affective computing—a field that turns 18 at the time of writing. This introductory chapter is intended to convey the motivations of the editors and content of the chapters in order to orient the readers to the handbook. It begins with a very high overview of the field of affective computing along with a bit of reminiscence about its formation, short history, and major accomplishments. The five main sections of the handbook—history and theory, detection, generation, methodologies, and applications—are then discussed, along with a bird’s eye view of the 41 chapters covered in the book. The introduction is devoted to short descriptions of the chapters featured in the handbook. A brief descript of the Glossary concludes the Introduction.},
keywords = {},
pubstate = {published},
tppubtype = {book}
}
The Oxford Handbook of Affective Computing aims to be the definite reference for research in the burgeoning field of affective computing—a field that turns 18 at the time of writing. This introductory chapter is intended to convey the motivations of the editors and content of the chapters in order to orient the readers to the handbook. It begins with a very high overview of the field of affective computing along with a bit of reminiscence about its formation, short history, and major accomplishments. The five main sections of the handbook—history and theory, detection, generation, methodologies, and applications—are then discussed, along with a bird’s eye view of the 41 chapters covered in the book. The introduction is devoted to short descriptions of the chapters featured in the handbook. A brief descript of the Glossary concludes the Introduction.
515.
Venek, Verena; Scherer, Stefan; Morency, Louis-Philippe; Rizzo, Albert; Pestian, John
ADOLESCENT SUICIDAL RISK ASSESSMENT IN CLINICIAN-PATIENT INTERACTION: A STUDY OF VERBAL AND ACOUSTIC BEHAVIORS Proceedings Article
In: Spoken Language Technology Workshop (SLT), 2014 IEEE, pp. 277–282, IEEE, South Lake Tahoe, NV, 2014, ISBN: 978-1-4799-7129-9.
@inproceedings{venek_adolescent_2014,
title = {ADOLESCENT SUICIDAL RISK ASSESSMENT IN CLINICIAN-PATIENT INTERACTION: A STUDY OF VERBAL AND ACOUSTIC BEHAVIORS},
author = {Verena Venek and Stefan Scherer and Louis-Philippe Morency and Albert Rizzo and John Pestian},
url = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=7078587},
doi = {10.1109/SLT.2014.7078587},
isbn = {978-1-4799-7129-9},
year = {2014},
date = {2014-12-01},
booktitle = {Spoken Language Technology Workshop (SLT), 2014 IEEE},
pages = {277–282},
publisher = {IEEE},
address = {South Lake Tahoe, NV},
abstract = {Suicide among adolescents is a major public health problem: it is the third leading cause of death in the US for ages 13-18. Up to now, there is no objective ways to assess the suicidal risk, i.e. whether a patient is non-suicidal, suicidal re-attempter (i.e. repeater) or suicidal non-repeater (i.e. individuals with one suicide attempt or showing signs of suicidal gestures or ideation). Therefore, features of the conversation including verbal information and nonverbal acoustic information were investigated from 60 audio-recorded interviews of 30 suicidal (13 repeaters and 17 non-repeaters) and 30 non-suicidal adolescents interviewed by a social worker. The interaction between clinician and patients was statistically analyzed to reveal differences between suicidal vs. non-suicidal adolescents and to investigate suicidal repeaters' behaviors in comparison to suicidal non-repeaters. By using a hierarchical ensemble classifier we were able to successfully discriminate non-suicidal patients, suicidal repeaters and suicidal non-repeaters.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Suicide among adolescents is a major public health problem: it is the third leading cause of death in the US for ages 13-18. Up to now, there is no objective ways to assess the suicidal risk, i.e. whether a patient is non-suicidal, suicidal re-attempter (i.e. repeater) or suicidal non-repeater (i.e. individuals with one suicide attempt or showing signs of suicidal gestures or ideation). Therefore, features of the conversation including verbal information and nonverbal acoustic information were investigated from 60 audio-recorded interviews of 30 suicidal (13 repeaters and 17 non-repeaters) and 30 non-suicidal adolescents interviewed by a social worker. The interaction between clinician and patients was statistically analyzed to reveal differences between suicidal vs. non-suicidal adolescents and to investigate suicidal repeaters' behaviors in comparison to suicidal non-repeaters. By using a hierarchical ensemble classifier we were able to successfully discriminate non-suicidal patients, suicidal repeaters and suicidal non-repeaters.
516.
Fyffe, Graham; Jones, Andrew; Alexander, Oleg; Ichikari, Ryosuke; Debevec, Paul
Driving High-Resolution Facial Scans with Video Performance Capture Journal Article
In: ACM Transactions on Graphics (TOG), vol. 34, no. 1, pp. 1– 13, 2014.
@article{fyffe_driving_2014,
title = {Driving High-Resolution Facial Scans with Video Performance Capture},
author = {Graham Fyffe and Andrew Jones and Oleg Alexander and Ryosuke Ichikari and Paul Debevec},
url = {http://ict.usc.edu/pubs/Driving%20High-Resolution%20Facial%20Scans%20with%20Video%20Performance%20Capture.pdf},
year = {2014},
date = {2014-11-01},
journal = {ACM Transactions on Graphics (TOG)},
volume = {34},
number = {1},
pages = {1– 13},
abstract = {We present a process for rendering a realistic facial performance with control of viewpoint and illumination. The performance is based on one or more high-quality geometry and reflectance scans of an actor in static poses, driven by one or more video streams of a performance. We compute optical flow correspondences between neighboring video frames, and a sparse set of correspondences between static scans and video frames. The latter are made possible by leveraging the relightability of the static 3D scans to match the viewpoint(s) and appearance of the actor in videos taken in arbitrary environments. As optical flow tends to compute proper correspondence for some areas but not others, we also compute a smoothed, per-pixel confidence map for every computed flow, based on normalized cross-correlation. These flows and their confidences yield a set of weighted triangulation constraints among the static poses and the frames of a performance. Given a single artist-prepared face mesh for one static pose, we optimally combine the weighted triangulation constraints, along with a shape regularization term, into a consistent 3D geometry solution over the entire performance that is drift free by construction. In contrast to previous work, even partial correspondences contribute to drift minimization, for example, where a successful match is found in the eye region but not the mouth. Our shape regularization employs a differential shape term based on a spatially varying blend of the differential shapes of the static poses and neighboring dynamic poses, weighted by the associated flow confidences. These weights also permit dynamic reflectance maps to be produced for the performance by blending the static scan maps. Finally, as the geometry and maps are represented on a consistent artist-friendly mesh, we render the resulting high-quality animated face geometry and animated reflectance maps using standard rendering tools.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
We present a process for rendering a realistic facial performance with control of viewpoint and illumination. The performance is based on one or more high-quality geometry and reflectance scans of an actor in static poses, driven by one or more video streams of a performance. We compute optical flow correspondences between neighboring video frames, and a sparse set of correspondences between static scans and video frames. The latter are made possible by leveraging the relightability of the static 3D scans to match the viewpoint(s) and appearance of the actor in videos taken in arbitrary environments. As optical flow tends to compute proper correspondence for some areas but not others, we also compute a smoothed, per-pixel confidence map for every computed flow, based on normalized cross-correlation. These flows and their confidences yield a set of weighted triangulation constraints among the static poses and the frames of a performance. Given a single artist-prepared face mesh for one static pose, we optimally combine the weighted triangulation constraints, along with a shape regularization term, into a consistent 3D geometry solution over the entire performance that is drift free by construction. In contrast to previous work, even partial correspondences contribute to drift minimization, for example, where a successful match is found in the eye region but not the mouth. Our shape regularization employs a differential shape term based on a spatially varying blend of the differential shapes of the static poses and neighboring dynamic poses, weighted by the associated flow confidences. These weights also permit dynamic reflectance maps to be produced for the performance by blending the static scan maps. Finally, as the geometry and maps are represented on a consistent artist-friendly mesh, we render the resulting high-quality animated face geometry and animated reflectance maps using standard rendering tools.
517.
Ghosh, Sayan; Chatterjee, Moitreya; Morency, Louis-Philippe
A Multimodal Context-based Approach for Distress Assessment Proceedings Article
In: Proceedings of the 16th International Conference on Multimodal Interaction, pp. 240–246, ACM Press, Istanbul, Turkey, 2014, ISBN: 978-1-4503-2885-2.
@inproceedings{ghosh_multimodal_2014,
title = {A Multimodal Context-based Approach for Distress Assessment},
author = {Sayan Ghosh and Moitreya Chatterjee and Louis-Philippe Morency},
url = {http://dl.acm.org/citation.cfm?doid=2663204.2663274},
doi = {10.1145/2663204.2663274},
isbn = {978-1-4503-2885-2},
year = {2014},
date = {2014-11-01},
booktitle = {Proceedings of the 16th International Conference on Multimodal Interaction},
pages = {240–246},
publisher = {ACM Press},
address = {Istanbul, Turkey},
abstract = {The increasing prevalence of psychological distress disorders, such as depression and post-traumatic stress, necessitates a serious effort to create new tools and technologies to help with their diagnosis and treatment. In recent years, new computational approaches were proposed to objectively analyze patient non-verbal behaviors over the duration of the entire interaction between the patient and the clinician. In this paper, we go beyond non-verbal behaviors and propose a tri-modal approach which integrates verbal behaviors with acoustic and visual behaviors to analyze psychological distress during the course of the dyadic semi-structured interviews. Our approach exploits the advantages of the dyadic nature of these interactions to contextualize the participant responses based on the affective components (intimacy and polarity levels) of the questions. We validate our approach using one of the largest corpus of semi-structured interviews for distress assessment which consists of 154 multimodal dyadic interactions. Our results show significant improvement on distress prediction performance when integrating verbal behaviors with acoustic and visual behaviors. In addition, our analysis shows that contextualizing the responses improves the prediction performance, most significantly with positive and intimate questions.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
The increasing prevalence of psychological distress disorders, such as depression and post-traumatic stress, necessitates a serious effort to create new tools and technologies to help with their diagnosis and treatment. In recent years, new computational approaches were proposed to objectively analyze patient non-verbal behaviors over the duration of the entire interaction between the patient and the clinician. In this paper, we go beyond non-verbal behaviors and propose a tri-modal approach which integrates verbal behaviors with acoustic and visual behaviors to analyze psychological distress during the course of the dyadic semi-structured interviews. Our approach exploits the advantages of the dyadic nature of these interactions to contextualize the participant responses based on the affective components (intimacy and polarity levels) of the questions. We validate our approach using one of the largest corpus of semi-structured interviews for distress assessment which consists of 154 multimodal dyadic interactions. Our results show significant improvement on distress prediction performance when integrating verbal behaviors with acoustic and visual behaviors. In addition, our analysis shows that contextualizing the responses improves the prediction performance, most significantly with positive and intimate questions.
518.
Park, Sunghyun; Shim, Han Suk; Chatterjee, Moitreya; Sagae, Kenji; Morency, Louis-Philippe
Computational Analysis of Persuasiveness in Social Multimedia: A Novel Dataset and Multimodal Prediction Approach Proceedings Article
In: Proceedings of the 16th International Conference on Multimodal Interaction, pp. 50–57, ACM Press, 2014, ISBN: 978-1-4503-2885-2.
@inproceedings{park_computational_2014,
title = {Computational Analysis of Persuasiveness in Social Multimedia: A Novel Dataset and Multimodal Prediction Approach},
author = {Sunghyun Park and Han Suk Shim and Moitreya Chatterjee and Kenji Sagae and Louis-Philippe Morency},
url = {http://dl.acm.org/citation.cfm?doid=2663204.2663260},
doi = {10.1145/2663204.2663260},
isbn = {978-1-4503-2885-2},
year = {2014},
date = {2014-11-01},
booktitle = {Proceedings of the 16th International Conference on Multimodal Interaction},
pages = {50–57},
publisher = {ACM Press},
abstract = {Our lives are heavily influenced by persuasive communication, and it is essential in almost any types of social interactions from business negotiation to conversation with our friends and family. With the rapid growth of social multimedia websites, it is becoming ever more important and useful to understand persuasiveness in the context of social multimedia content online. In this paper, we introduce our newly created multimedia corpus of 1,000 movie review videos obtained from a social multimedia website called ExpoTV.com, which will be made freely available to the research community. Our research results presented here revolve around the following 3 main research hypotheses. Firstly, we show that computational descriptors derived from verbal and nonverbal behavior can be predictive of persuasiveness. We further show that combining descriptors from multiple communication modalities (audio, text and visual) improve the prediction performance compared to using those from single modality alone. Secondly, we investigate if having prior knowledge of a speaker expressing a positive or negative opinion helps better predict the speaker's persuasiveness. Lastly, we show that it is possible to make comparable prediction of persuasiveness by only looking at thin slices (shorter time windows) of a speaker's behavior.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Our lives are heavily influenced by persuasive communication, and it is essential in almost any types of social interactions from business negotiation to conversation with our friends and family. With the rapid growth of social multimedia websites, it is becoming ever more important and useful to understand persuasiveness in the context of social multimedia content online. In this paper, we introduce our newly created multimedia corpus of 1,000 movie review videos obtained from a social multimedia website called ExpoTV.com, which will be made freely available to the research community. Our research results presented here revolve around the following 3 main research hypotheses. Firstly, we show that computational descriptors derived from verbal and nonverbal behavior can be predictive of persuasiveness. We further show that combining descriptors from multiple communication modalities (audio, text and visual) improve the prediction performance compared to using those from single modality alone. Secondly, we investigate if having prior knowledge of a speaker expressing a positive or negative opinion helps better predict the speaker's persuasiveness. Lastly, we show that it is possible to make comparable prediction of persuasiveness by only looking at thin slices (shorter time windows) of a speaker's behavior.
519.
Scherer, Stefan; Hammal, Zakia; Yang, Ying; Morency, Louis-Philippe; Cohn, Jeffrey F.
Dyadic Behavior Analysis in Depression Severity Assessment Interviews Proceedings Article
In: Proceedings of the 16th International Conference on Multimodal Interaction, pp. 112–119, ACM Press, Istanbul, Turkey, 2014, ISBN: 978-1-4503-2885-2.
@inproceedings{scherer_dyadic_2014,
title = {Dyadic Behavior Analysis in Depression Severity Assessment Interviews},
author = {Stefan Scherer and Zakia Hammal and Ying Yang and Louis-Philippe Morency and Jeffrey F. Cohn},
url = {http://dl.acm.org/citation.cfm?doid=2663204.2663238},
doi = {10.1145/2663204.2663238},
isbn = {978-1-4503-2885-2},
year = {2014},
date = {2014-11-01},
booktitle = {Proceedings of the 16th International Conference on Multimodal Interaction},
pages = {112–119},
publisher = {ACM Press},
address = {Istanbul, Turkey},
abstract = {Previous literature suggests that depression impacts vocal timing of both participants and clinical interviewers but is mixed with respect to acoustic features. To investigate further, 57 middle-aged adults (men and women) with Major Depression Disorder and their clinical interviewers (all women) were studied. Participants were interviewed for depression severity on up to four occasions over a 21 week period using the Hamilton Rating Scale for Depression (HRSD), which is a criterion measure for depression severity in clinical trials. Acoustic features were extracted for both participants and interviewers using COVAREP Toolbox. Missing data occurred due to missed appointments, technical problems, or insufficient vocal samples. Data from 36 participants and their interviewers met criteria and were included for analysis to compare between high and low depression severity. Acoustic features for participants varied between men and women as expected, and failed to vary with depression severity for participants. For interviewers, acoustic characteristics strongly varied with severity of the interviewee's depression. Accommodation - the tendency of interactants to adapt their communicative behavior to each other - between interviewers and interviewees was inversely related to depression severity. These findings suggest that interviewers modify their acoustic features in response to depression severity, and depression severity strongly impacts interpersonal accommodation.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Previous literature suggests that depression impacts vocal timing of both participants and clinical interviewers but is mixed with respect to acoustic features. To investigate further, 57 middle-aged adults (men and women) with Major Depression Disorder and their clinical interviewers (all women) were studied. Participants were interviewed for depression severity on up to four occasions over a 21 week period using the Hamilton Rating Scale for Depression (HRSD), which is a criterion measure for depression severity in clinical trials. Acoustic features were extracted for both participants and interviewers using COVAREP Toolbox. Missing data occurred due to missed appointments, technical problems, or insufficient vocal samples. Data from 36 participants and their interviewers met criteria and were included for analysis to compare between high and low depression severity. Acoustic features for participants varied between men and women as expected, and failed to vary with depression severity for participants. For interviewers, acoustic characteristics strongly varied with severity of the interviewee's depression. Accommodation - the tendency of interactants to adapt their communicative behavior to each other - between interviewers and interviewees was inversely related to depression severity. These findings suggest that interviewers modify their acoustic features in response to depression severity, and depression severity strongly impacts interpersonal accommodation.
520.
Nouri, Elnaz
Training Agents by Crowds Proceedings Article
In: Proceedings of HCOMP 2014, Pittsburgh, PA, 2014.
@inproceedings{nouri_training_2014,
title = {Training Agents by Crowds},
author = {Elnaz Nouri},
url = {http://ict.usc.edu/pubs/Training%20Agents%20by%20Crowds.pdf},
year = {2014},
date = {2014-11-01},
booktitle = {Proceedings of HCOMP 2014},
address = {Pittsburgh, PA},
abstract = {On-line learning algorithms are particularly suitable for developing interactive computational agents. These algorithm can be used to teach the agents the abilities needed for engaging in social interactions with humans. If humans are used as teachers in the context of on-line learning algorithms a serious challenge arises: their lack of commitment and availability during the required extensive training. In this work we address this challenge by showing how ”crowds of human workers” rather than ”single users” can be recruited as teachers for training each learning agent. This paper proposes a framework for training agents by the crowds. The focus of this proposal is narrowed by using Reinforcement Learning as the human guidance method for teaching agents how to engage in simple negotiation games (such as the Ultimatum Bargaining Game and the Dictator Game).},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
On-line learning algorithms are particularly suitable for developing interactive computational agents. These algorithm can be used to teach the agents the abilities needed for engaging in social interactions with humans. If humans are used as teachers in the context of on-line learning algorithms a serious challenge arises: their lack of commitment and availability during the required extensive training. In this work we address this challenge by showing how ”crowds of human workers” rather than ”single users” can be recruited as teachers for training each learning agent. This paper proposes a framework for training agents by the crowds. The focus of this proposal is narrowed by using Reinforcement Learning as the human guidance method for teaching agents how to engage in simple negotiation games (such as the Ultimatum Bargaining Game and the Dictator Game).
Filter
Sorry, no publications matched your criteria.