The DOI matches its Crossref record.
Affective Computing
Open accessAbstract
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. 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.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“In contrast, the goal of our system was to use on-body sensors with EDA and electrocardiogram (EKG), since these sensors have been shown to be reliable for emotion detection [14,17,18].”
From Food and Mood: Just-in-Time Support for Emotional Eating (2013) · cites this paper as [18]
Citations
Cited by
Sorted by citations
Items 3,401–3,500 of 7,380
Multimodal Emotion Analysis of Robotic Assistance in Elderly Care
Demaeght, A., Miclau, C., Hartmann, J., Markwardt, J., & Korn, O. (2022) · International Conference on PErvasive Technologies Related to Assistive Environments (PETRA) · doi:10.1145/3529190.3529194 · Cited by 9
Ethical Awareness in Paralinguistics: A Taxonomy of Applications
Batliner, A. M., Neumann, M., Burkhardt, F., Baird, A., Meyer, S., Vu, N. T., & Schuller, B. W. (2022) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2022.2140385 · Cited by 9
Bro-cam: Improving Game Experience with Empathic Feedback Using Posture Tracking
Tan, C. S. S., Schöning, J., Barnes, J. S., Luyten, K., & Coninx, K. (2013) · Lecture notes in computer science · doi:10.1007/978-3-642-37157-8_27 · Cited by 9
Emotion regulation in management: Harnessing the potential of NeuroIS tools
Gimpel, H., Adam, M. T. P., & Teubner, T. (2013) · ERef Bayreuth (University of Bayreuth) · Cited by 9
Using interval type-2 fuzzy logic to analyze Turkish emotion words
Cakmak, O., Kazemzadeh, A., Yıldırım, S., & Narayanan, S. R. (2012) · Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC) · Cited by 9
A Study of How to Implement a Listener Estimate Emotion in Speech
Kurematsu, M., Marina, O., 木下, お., Hakura, J., & Fujita, H. (2009) · Frontiers in artificial intelligence and applications · doi:10.3233/978-1-60750-049-0-531 · Cited by 9
Dóris 3D: Agente Pedagógico baseado em Emoções
Frozza, R., da Silva, A. K., Lux, B., da Cruz, M. E. J. K., & Borin, M. P. (2009) · Anais do ... Simpósio Brasileiro de Informática na Educação/Anais do Simpósio Brasileiro de Informática na Educação · Cited by 9
The effects of seductive augmentation and agent role on learning interest, achievement, and attitude
Keller, J. M., & Park, S. (2005) · Cited by 9
Affective Embodied Conversational Agents for Natural Interaction
Cerezo, E., Baldassarri, S., Hupont, I., & Francisco, J. (2008) · doi:10.5772/6173 · Cited by 9
A Robot Emotion Generation Mechanism Based on PAD Emotion Space
Qing-ji, G., Wang, K., & Haijuan, L. (2008) · IFIP International Federation for Information Processing/IFIP · doi:10.1007/978-0-387-87685-6_18 · Cited by 9
Reality-Based Brain-Computer Interaction
Sjölie, D., Eriksson, J., Bodin, K., & Janlert, L.-E. (2010) · doi:10.13140/2.1.1565.2800 · Cited by 9
Detecting Emotions in Social Affective Situations Using the EmotiNet Knowledge Base
Balahur, A., Hermida, J. M., & Montoyo, A. (2011) · Lecture notes in computer science · doi:10.1007/978-3-642-21111-9_69 · Cited by 9
Agents, emergence, emotion and representation
Davis, D. N. (2002) · Annual Conference of the IEEE Industrial Electronics Society (IECON) · doi:10.1109/iecon.2000.972404 · Cited by 9
Physical contact using haptic and gestural expressions for ubiquitous partner robot
Yonezawa, T., Yamazoe, H., & Abe, S. (2013) · IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · doi:10.1109/iros.2013.6697179 · Cited by 9
Introducing active learning on Text to Emotion Analyzer
Asad, M.-U., Afroz, N., Dey, L., Nath, R. P. D., & Azim, M. A. (2014) · International Conference on Computer and Information Technology (ICCIT) · doi:10.1109/iccitechn.2014.7073079 · Cited by 9
Speech emotion recognition using modified quadratic discrimination function
Zhao, Y. C., Zhao, L., Zou, C., & Yu, Y. (2008) · Journal of Electronics (China) · doi:10.1007/s11767-008-0041-8 · Cited by 9
Implicit affective profiling of subjects based on physiological data coupling
Kroupi, E., Vesin, J., & Ebrahimi, T. (2014) · Brain-Computer Interfaces · doi:10.1080/2326263x.2014.912882 · Cited by 9
Research on predicting models of annoyance under the operation of digital hi-tech products
Huang, J.-S., Ma, M.-Y., & Chen, C. (2006) · Design Studies · doi:10.1016/j.destud.2006.09.002 · Cited by 9
Speaker identification in emotional talking environments using both gender and emotion cues
Shahin, I. M. A. (2013) · International Conference on Communications, Signal Processing, and their Applications (ICCSPA) · doi:10.1109/iccspa.2013.6487314 · Cited by 9
Integrating User Affective State Assessment in Enhancing HCI: Review and Proposition
Li, X. (2008) · The Open Cybernetics & Systemics Journal · doi:10.2174/1874110x00802010192 · Cited by 9
Topics in Biometric Human-Machine Interaction Security
Kannavara, R., & Shippy, K. L. (2013) · IEEE Potentials · doi:10.1109/mpot.2013.2248891 · Cited by 9
Anttonen, J., Surakka, V., & Koivuluoma, M. (2009) · Journal of Media Psychology Theories Methods and Applications · doi:10.1027/1864-1105.21.2.69 · Cited by 10
Fiction support for realistic portrayals of fear-type emotional manifestations
Clavel, C., Vasilescu, I., & Devillers, L. Y. (2010) · Computer Speech & Language · doi:10.1016/j.csl.2010.03.003 · Cited by 9
Simulation de la dynamique des émotions et des relations sociales de personnages virtuels
Ochs, M., Sabouret, N., & Corruble, V. (2009) · Revue d intelligence artificielle · doi:10.3166/ria.23.327-357 · Cited by 9
Utility and Experience in the Evolution of Usability
Lindgaard, G., & Parush, A. (2007) · Human-computer interaction series · doi:10.1007/978-1-84628-941-5_10 · Cited by 9
Applause as an achievement‐based reward during a computerised self‐assessment test
Moridis, C. N., & Economides, A. A. (2011) · British Journal of Educational Technology · doi:10.1111/j.1467-8535.2011.01221.x · Cited by 9
Measuring social behaviour as an indicator of experience
Lindley, S. E., & Monk, A. F. (2011) · Behaviour and Information Technology · doi:10.1080/0144929x.2011.582148 · Cited by 9
Supporting Empathy in Online Learning with Artificial Expressions
Lyons, M. J., Kluender, D., & Tetsutani, N. (2005) · Cited by 9
Using interval type-2 fuzzy logic to translate emotion words from Spanish to English
Kazemzadeh, A. (2010) · IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) · doi:10.1109/fuzzy.2010.5584884 · Cited by 9
Engaging human-to-robot attention using conversational gestures and lip-synchronization
Burgos, F. A. C., Manso, L. J., Calderita, L. V., Sánchez, A., & Trujillo, P. N. (2012) · Journal of Physical Agents (JoPha) · doi:10.14198/jopha.2012.6.1.02 · Cited by 9
An architecture for emotional and context-aware associative learning for robot companions
Raymundo, C. R., Johnson, C. G., & Vargas, P. A. (2015) · IEEE RO-MAN · doi:10.1109/roman.2015.7333699 · Cited by 9
Foundation of an affective tutoring system: learning how human tutors adapt to student emotion
Alexander, S., Sarrafzadeh, A., & Hill, S. (2008) · International Journal of Intelligent Systems Technologies and Applications · doi:10.1504/ijista.2008.017278 · Cited by 9
Empathy for max (preliminary project report)
Becker, C., Prendinger, H., Ishizuka, M., & Wachsmuth, I. (2005) · Active Media Technology · doi:10.1109/amt.2005.1505417 · Cited by 9
Virtual Reality and Affective Computing for Improving Learning
Ontiveros-Hernández, N. J., Pérez-Ramírez, M., & Hernández, Y. (2013) · Research in Computing Science · doi:10.13053/rcs-65-1-11 · Cited by 9
Zics, B. (2011) · Leonardo · doi:10.1162/leon_a_00090 · Cited by 9
Emotion recognition in natural scene images based on brain activity and gist
Zhang, Q., & Lee, M. (2008) · International Joint Conference on Neural Networks (IJCNN) · doi:10.1109/ijcnn.2008.4634229 · Cited by 9
Towards user-independent classification of multimodal emotional signals
Kim, J., André, E., & Vogt, T. (2009) · International Conference on Affective Computing and Intelligent Interaction and workshops · doi:10.1109/acii.2009.5349495 · Cited by 10
Mansoorizadeh, M., & Charkari, N. M. (2009) · International CSI Computer Conference (CSICC) · doi:10.1109/csicc.2009.5349653 · Cited by 10
iCat: an Affective Game Buddy Based on Anticipatory Mechanisms (Short Paper)
Leite, I., Martinho, C., Pereira, A., & Paiva, A. (2008) · Cited by 9
Speech Communication and Multimodal Interfaces
Schuller, B. W., Ablaßmeier, M., Müller, R., Reifinger, S., Poitschke, T., & Rigoll, G. (2006) · Springer eBooks · doi:10.1007/3-540-30619-6_4 · Cited by 9
Torpey, P. A., & Jessop, E. N. (2009) · CHI Conference Extended Abstracts on Human Factors in Computing Systems (CHI EA) · doi:10.1145/1520340.1520555 · Cited by 9
Emotion recognition of conversational affective speech using temporal course modeling
Lin, J., Wu, C., & Wei, W.-L. (2013) · Interspeech (USB) · doi:10.21437/interspeech.2013-354 · Cited by 9
Griffin, W. A., & Li, X. (2016) · PLoS ONE · doi:10.1371/journal.pone.0155706 · Cited by 10
From Monomodal to Multimodal: Affect Recognition Using Visual Modalities
Monekosso, D., Remagnino, P., & Kuno, Y. (2008) · Intelligent Environments · doi:10.1007/978-1-84800-346-0_10 · Cited by 9
Jain, S., & Asawa, K. (2015) · International Journal of Synthetic Emotions · doi:10.4018/ijse.2015070103 · Cited by 9
Assessment of Human Factors in Adaptive Hypermedia Environments
Tsianos, N., Germanakos, P., Lekkas, Z., & Mourlas, C. (2009) · Intelligent User Interfaces · doi:10.4018/978-1-60566-032-5.ch001 · Cited by 9
Expressiveness in Music Performance
Canazza, S., Poli, G. D., Rodà, A., & Vidolin, A. (2012) · IGI Global eBooks · doi:10.4018/978-1-4666-2497-9.ch008 · Cited by 9
Measuring emotions in interactive contexts
Kong, X., & Yang, Y. (2009) · IEEE International Conference on Computer-Aided Industrial Design & Conceptual Design · doi:10.1109/caidcd.2009.5374937 · Cited by 9
Workload management through glanceable feedback: The role of heart rate variability
Muñoz, J. E., Pereira, F., & Karapanos, E. (2016) · IEEE International Conference on e-Health Networking, Applications and Services (Healthcom) · doi:10.1109/healthcom.2016.7749477 · Cited by 8
Affective Behavior and Nonverbal Interaction in Collaborative Virtual Environments
Negrón, A. P. P., Rangel, N. E., Muñoz, M., Mejía, J., & Lara, G. (2016) · Educational Technology & Society · Cited by 9
Morrison, D. M., & Miller, K. B. (2017) · International Journal of Artificial Intelligence in Education · doi:10.1007/s40593-017-0153-0 · Cited by 9
Emotions Detection Through the Analysis of Physiological Information During Video Games Fruition
Granato, M., Gadia, D., Maggiorini, D., & Ripamonti, L. A. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-71940-5_18 · Cited by 9
Boger, J. N., Young, V., Jesse, H., Jiancaro, T., & Mihailidis, A. (2018) · Synthesis lectures on assistive, rehabilitative, and health-preserving technologies · doi:10.2200/s00826ed2v01y201802arh012 · Cited by 11
Sentiment Analysis for Microblog Related to Finance Based on Rules and Classification
Yan, D., Hu, B., & Qin, J. (2018) · IEEE International Conference on Big Data and Smart Computing (BigComp) · doi:10.1109/bigcomp.2018.00026 · Cited by 9
A functional data analysis approach for continuous 2-D emotion annotations
Sharma, K., Wagner, M., Castellini, C., van den Broek, E. L., Stulp, F., & Schwenker, F. (2019) · Web Intelligence · doi:10.3233/web-190399 · Cited by 9
An affective serious game for collaboration between humans and robots
Jerčić, P., Hagelbäck, J., & Lindley, C. A. (2019) · Entertainment Computing · doi:10.1016/j.entcom.2019.100319 · Cited by 9
An affective decision-making model with applications to social robotics
Liu, S., & Insua, D. R. (2019) · EURO Journal on Decision Processes · doi:10.1007/s40070-019-00109-1 · Cited by 9
Fusing hotel ratings and reviews with hesitant terms and consensus measures
Nguyen, J., Montserrat-Adell, J., Agell, N., Sánchez, M., & Ruiz, F. J. (2020) · Neural Computing and Applications · doi:10.1007/s00521-020-04778-x · Cited by 9
Emotions and Personality in Agent Design and Modeling
Gmytrasiewicz, P. J., & Lisetti, C. (2002) · Multiagent systems, artificial societies, and simulated organizations · doi:10.1007/978-1-4615-1107-6_5 · Cited by 10
Better Game Experience Through Game Metrics: A Rally Videogame Case Study
Guardini, P., & Maninetti, P. (2013) · Springer eBooks · doi:10.1007/978-1-4471-4769-5_16 · Cited by 9
Emotional intelligence in interactive systems
Angeli, A. D., & Johnson, G. I. (2003) · CRC Press eBooks · doi:10.1201/9780203608173-c48 · Cited by 9
Emotion recognition from speech using extended feature selection and a simple classifier
Hassan, A., & Damper, R. I. (2009) · Interspeech (USB) · doi:10.21437/interspeech.2009-587 · Cited by 9
Designing for ease is designing for all
Destounis, P., Garofalakis, J. D., Mavritsakis, G., Rigou, M., Sirmakessis, S., & Tzimas, G. E. (2004) · Information Technology and People · doi:10.1108/09593840410554193 · Cited by 9
Affect Transfer by Metaphor for an Intelligent Conversational Agent
Wallington, A. M., Agerri, R., Barnden, J. A., Lee, M. G., & Rumbell, T. H. (2011) · Text, speech and language technology · doi:10.1007/978-94-007-1757-2_5 · Cited by 9
Market efficiency from an evolutionary perspective.
Lo, A. W. (2004) · Cited by 9
Statistical Approach for a Complex Emotion Recognition Based on EEG Features
Handayani, D. O. D., Yaacob, H. S., Wahab, A., & Alshaikhli, I. F. T. (2015) · International Conference on Advanced Computer Science Applications and Technologies · doi:10.1109/acsat.2015.54 · Cited by 9
Natural emotion elicitation for emotion modeling in child-robot interactions.
Wang, W., Αθανασόπουλος, Γ., Yilmazyildiz, S., Patsis, G., Enescu, V., Hichem Sahli, B., Verhelst, W., Hiolle, A., Lewis, M., & Cañamero, L. D. (2014) · VUBIR (Vrije Universiteit Brussel) · Cited by 9
The Emotional Computer Adaptive to Human Emotion
Whang, M. (2007) · Philips Research · doi:10.1007/978-1-4020-6593-4_18 · Cited by 9
Aesthetic forms of expression as information delivery units
Nemirovsky, P., & Davenport, G. (2002) · Advances in consciousness research · doi:10.1075/aicr.35.24nem · Cited by 9
Emergent Affective and Personality Model
Lim, M., Aylett, R., & Jones, C. (2005) · International Conference on Intelligent Virtual Agents · doi:10.1007/11550617_31 · Cited by 17
Toward ubiquitous intelligent robotics
Kogure, K., Hagita, N., Sumi, Y., Kuwahara, N., & Ishiguro, H. (2004) · IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · doi:10.1109/iros.2003.1248909 · Cited by 9
Exploitation in Affect Detection in Improvisational E-Drama
Zhang, L., Barnden, J. A., Hendley, R., & Wallington, A. M. (2006) · Lecture notes in computer science · doi:10.1007/11821830_6 · Cited by 9
Designing Agents for a Virtual Marketplace
Kamyab, F., Guérin, F., Goulev, P., & Mamdani, E. H. (2001) · Artificial Intelligence and the Simulation of Behaviour · Cited by 9
Redrawing the Link Between Customer Satisfaction and Speech Quality
Gros, L., Durin, V., & Chateau, N. (2008) · Acta acustica united with Acustica · doi:10.3813/aaa.918005 · Cited by 9
A Hybrid Robot Navigation Approach Based on Partial Planning and Emotion-Based Behavior Coordination
Zhang, H., Liu, S., & Yang, S. X. (2006) · IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · doi:10.1109/iros.2006.281851 · Cited by 9
Affective feedback in closed loop human-robot interaction
Rani, P., Liu, C., & Sarkar, N. (2006) · ACM/IEEE International Conference on Human-Robot Interaction (HRI) · doi:10.1145/1121241.1121303 · Cited by 9
Designing for human emotion: ways of knowing
Lottridge, D. M., & Moore, G. (2009) · New Review of Hypermedia and Multimedia · doi:10.1080/13614560903165136 · Cited by 9
Interacting with an artificial partner: modeling the role of emotional aspects
Cattinelli, I., Goldwurm, M., & Borghese, N. A. (2008) · Biological Cybernetics · doi:10.1007/s00422-008-0254-9 · Cited by 9
Affective Cognitive Modeling for Autonomous Agents Based on Scherer’s Emotion Theory
Lisetti, C., & Marpaung, A. H. (2007) · Springer eBooks · doi:10.1007/978-3-540-69912-5_3 · Cited by 9
Broadening the Scope of Affect Detection Research
Reisenzein, R. (2010) · IEEE Transactions on Affective Computing · doi:10.1109/t-affc.2010.9 · Cited by 9
Sloman, A. (1998) · Cited by 9
Empathic Interaction with a Virtual Guide
Aylett, R. S., Lim, M. Y., & Jones, C. M. (2005) · Cited by 9
Neural network and wavelet recognition of facial electromyographic signals.
Laakso, J., Juhola, M., Surakka, V., Aula, A., & Partala, T. (2001) · PubMed · Cited by 9
Kanis, M., & Brinkman, W. (2007) · European Conference on Cognitive Ergonomics · doi:10.1145/1362550.1362589 · Cited by 9
Emotional attributes in autonomic computing systems
Lee, A., & Ibrahim, M. (2004) · International Workshop on Database and Expert Systems Applications (DEXA) · doi:10.1109/dexa.2003.1232100 · Cited by 8
An emotion-based agent architecture
Sarmento, L. (2004) · Portuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT) · doi:10.34626/fd4j-9v92 · Cited by 9
A face-house paradigm for architectural scene analysis
Chalup, S. K., Hong, K., & Ostwald, M. J. (2008) · Conference on Soft Computing as Transdisciplinary Science and Technology · doi:10.1145/1456223.1456304 · Cited by 9
Prosodic Font : the space between the spoken and the written
Shankar, T. R. (1998) · DSpace@MIT (Massachusetts Institute of Technology) · Cited by 9
Predicting Performance Under Stressful Conditions Using Galvanic Skin ResponsePreprint
Mundell, C., Vielma, J. P., & Zaman, T. R. (2016) · arXiv (Cornell University) · doi:10.48550/arxiv.1606.01836 · Cited by 9
Sentiment Analysis of Microblogging Data
Basile, P., Basile, V., Nissim, M., Novielli, N., & Patti, V. (2017) · Springer eBooks · doi:10.1007/978-1-4614-7163-9_110168-1 · Cited by 9
Feng, K., & Chaspari, T. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2006.03001 · Cited by 10
A Multi-Context Emotional EEG Dataset for Cross-Context Emotion Decoding
Xu, X., Shen, X., Chen, X., Zhang, Q., Wang, S., Li, Y., Li, Z., Zhang, D., Zhang, M., & Liu, Q. (2025) · Scientific Data · doi:10.1038/s41597-025-05349-2 · Cited by 11
Evaluation multimodaler Computer-Systeme in frühen Entwicklungsphasen
Seifert, K. (2002) · DepositOnce · doi:10.14279/depositonce-530 · Cited by 9
Inferring mental overload based on postural behavior and gestures
Hihn, H., Meudt, S., & Schwenker, F. (2016) · Proceedings of the 2nd workshop on Emotion Representations and Modelling for Companion Systems · doi:10.1145/3009960.3009961 · Cited by 8
Real-Time Quality Index to Control Data Loss in Real-Life Cardiac Monitoring Applications
Vila, G., Godin, C., Charbonnier, S., & Campagne, A. (2021) · Sensors · doi:10.3390/s21165357 · Cited by 8
AmbiDots: An Ambient Interface to Mediate Casual Social Settings through Peripheral Interaction
Thompson, E., Potts, D., Hardy, J., Porter, B., & Houben, S. (2021) · Australian Conference on Human-Computer Interaction (OzCHI) · doi:10.1145/3520495.3520504 · Cited by 8
D’Amelio, T. A., Bruno, N. M., Bugnon, L. A., Zamberlán, F., & Tagliazucchi, E. (2023) · International Conference on Affective Computing and Intelligent Interaction Workshops and Demos (ACIIW) · doi:10.1109/aciiw59127.2023.10388155 · Cited by 8
I DARE: IULM Dataset of Affective Responses
Bilucaglia, M., Zito, M., Fici, A., Casiraghi, C., Rivetti, F., Bellati, M., & Russo, V. (2024) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2024.1347327 · Cited by 8
Multi-Task Emotion Recognition Based on Dimensional Model and Category Label
Huo, Y., & Ge, Y. J. (2024) · IEEE Access · doi:10.1109/access.2024.3404990 · Cited by 8
From Extraction to Generation: Multimodal Emotion-Cause Pair Generation in Conversations
Ma, H., Yu, J., Wang, F., Cao, H., & Xia, R. (2024) · IEEE Transactions on Affective Computing · doi:10.1109/taffc.2024.3446646 · Cited by 9
Metadata
- Authors
- Picard, R. W.
- Affiliations
- MIT Media Lab (US)
- Corresponding author
- Picard, Rosalind W.
- ORCID
- Picard, Rosalind W.
- Venue
- MIT Press
- Publisher
- The MIT Press
- Published
- 1997-09-24
- OpenAlex
- W2339343773
- Cited by
- 7,382
- References
- 0
- Citations by year
- 2026: 376 · 2025: 295 · 2024: 212 · 2023: 266 · 2022: 208 · 2021: 274 · 2020: 322 · 2019: 356 · 2018: 283 · 2017: 279 · 2016: 301 · 2015: 318 · 2014: 315 · 2013: 335 · 2012: 329
- FWCI
- 92.96
- Type
- book
- Language
- en
- Open access
- green
- hdl.handle.net
- Licence
- cc-by-nc-sa
- Locations
- The MIT Press eBooks (publishedVersion)
- PsycEXTRA Dataset (publishedVersion)
- DSpace@MIT (Massachusetts Institute of Technology) (submittedVersion, cc-by-nc-sa)
- DSpace@MIT (Massachusetts Institute of Technology) (submittedVersion, cc-by-nc)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Emotion and Mood Recognition
- Physical Sciences › Computer Science › Human-Computer Interaction › Innovative Human-Technology Interaction
- Physical Sciences › Computer Science › Artificial Intelligence › Psychiatry, Mental Health, Neuroscience
- Keywords
- affective computing, emotion recognition, emotion models, emotion synthesis, wearable computers, human-computer interaction, decision-making, pattern recognition
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review