Affective Computing

Towards EEG-based BCI driven by emotions for addressing BCI-Illiteracy: a meta-analytic review

Spezialetti, M., Cinque, L., Tavares, J. M. R. S., & Placidi, G. (2018) · Behaviour and Information Technology · doi:10.1080/0144929x.2018.1485745 · Cited by 32

Biosensing and Actuation—Platforms Coupling Body Input-Output Modalities for Affective Technologies

Alfaras, M., Primett, W., Umair, M., Windlin, C., Karpashevich, P., Chalabianloo, N., Bowie-DaBreo, D., Sas, C., Sanches, P., Höök, K., et al. (2020) · Sensors · doi:10.3390/s20215968 · Cited by 37

A Literature Review of EEG-Based Affective Computing in Marketing

Pei, G.-X., & Li, T. (2021) · Frontiers in Psychology · doi:10.3389/fpsyg.2021.602843 · Cited by 27

Text-Based Emotion Recognition in English and Polish for Therapeutic Chatbot

Zygadło, A., Kozłowski, M., & Janicki, A. (2021) · Applied Sciences · doi:10.3390/app112110146 · Cited by 30

A Dog Tail for Utility Robots: Exploring Affective Properties of Tail Movement

Singh, A., & Young, J. E. (2013) · Lecture notes in computer science · doi:10.1007/978-3-642-40480-1_27 · Cited by 30

Computing Emotion Awareness Through Facial Electromyography

van den Broek, E. L., Schut, M. H., Westerink, J. H. D. M., van Herk, J., & Tuinenbreijer, K. (2006) · Lecture notes in computer science · doi:10.1007/11754336_6 · Cited by 30

HCI and the Face: Towards an Art of the Soluble

Bartneck, C., & Lyons, M. J. (2007) · Springer eBooks · doi:10.1007/978-3-540-73105-4_3 · Cited by 30

Non-Intrusive Measurement of Workload in Real-Time

Guhe, M., Gray, W. D., Schoelles, M. J., Liao, W., Zhu, Z., & Ji, Q. (2005) · Proceedings of the Human Factors and Ergonomics Society Annual Meeting · doi:10.1177/154193120504901213 · Cited by 30

Emotion Recognition System in Images Based On Fuzzy Neural Network and HMM

Guo, Y., & Gao, H. (2006) · IEEE International Conference on Cognitive Informatics · doi:10.1109/coginf.2006.365679 · Cited by 30

Embodying care in Matilda

Khosla, R., Chu, M.-T., Kachouie, R., Yamada, K., & Yamaguchi, T. (2012) · International Health Informatics Symposium · doi:10.1145/2110363.2110398 · Cited by 30

Communication and Automatic Interpretation of Affect from Facial Expressions

Salah, A. A., Sebe, N., & Gevers, T. (2011) · IGI Global eBooks · doi:10.4018/978-1-61692-892-6.ch008 · Cited by 30

Stress in interactive applications: analysis of the valence-arousal space based on physiological signals and self-reported data

Liapis, A., Katsanos, C., Sotiropoulos, D. G., Καρούσος, Ν., & Xenos, M. (2016) · Multimedia Tools and Applications · doi:10.1007/s11042-016-3637-2 · Cited by 32

KANSEI and Robotics. Mental Commit Robot for Healing Human Mind.

Shibata, T. (1999) · Journal of the Robotics Society of Japan · doi:10.7210/jrsj.17.943 · Cited by 30

Online feedback system for public speakers

Nguyen, A.-T., Chen, W., & Matthias Rauterberg, A. (2012) · IEEE Conference on e-Learning, e-Management and e-Services (IC3e) · doi:10.1109/is3e.2012.6414963 · Cited by 30

Gender and emotion recognition with implicit user signals

Bilalpur, M., Kia, S. M., Chawla, M., Chua, T., & Subramanian, R. (2017) · INTERNATIONAL CONFERENCE ON MULTIMODAL INTERACTION · doi:10.1145/3136755.3136790 · Cited by 30

Player-Game Interaction Through Affective Sound

Nacke, L. E., & Grimshaw, M. (2010) · IGI Global eBooks · doi:10.4018/978-1-61692-828-5.ch013 · Cited by 30

Building HAL: computers that sense, recognize, and respond to human emotion

Picard, R. W. (2001) · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · doi:10.1117/12.429523 · Cited by 30

aMAZEd

Mahmud, A. A., Mubin, O., Octavia, J. R., Shahid, S., Yeo, L., Markopoulos, P., & Martens, J.-B. (2007) · ACM International Conference on Interaction Design and Children (IDC) · doi:10.1145/1297277.1297287 · Cited by 30

From rational to emotional agents

Vidal, J. M., & Jiang, H. (2007) · Cited by 30

A digital photography framework enabling affective awareness in home communication

Liechti, O., & Ichikawa, T. (2000) · Personal Technologies · doi:10.1007/bf01613595 · Cited by 30

Context Awareness in Information Logistics

Haseloff, S. (2005) · DepositOnce · doi:10.14279/depositonce-1044 · Cited by 30

Intelligent Notification Systems: A Survey of the State of the Art and Research ChallengesPreprint

Mehrotra, A., & Musolesi, M. (2017) · arXiv (Cornell University) · doi:10.48550/arxiv.1711.10171 · Cited by 30

Sentiment analysis meets social media – Challenges and solutions of the field in view of the current information sharing context

Balahur, A., & Jacquet, G. (2015) · Information Processing & Management · doi:10.1016/j.ipm.2015.05.005 · Cited by 30

Visions of Artificial Intelligence and Robots in Science Fiction: a computational analysis

Ōsawa, H., Miyamoto, D., Hase, S., Saijo, R., Fukuchi, K., & Miyake, Y. (2022) · International Journal of Social Robotics · doi:10.1007/s12369-022-00876-z · Cited by 29

Shaping the Future of Destinations: New Clues to Smart Tourism Research from a Neuroscience Methods Approach

Cardoso, L., & Fraga, C. (2024) · Administrative Sciences · doi:10.3390/admsci14060106 · Cited by 29

Highlight Detection in Movie Scenes Through Inter-users, Physiological Linkage

Chênes, C., Chanel, G., Soleymani, M., & Pun, T. (2012) · Computer communications and networks · doi:10.1007/978-1-4471-4555-4_10 · Cited by 29

User Psychology: Re-assessing the Boundaries of a Discipline

Saariluoma, P. O., & Oulasvirta, A. (2010) · Psychology · doi:10.4236/psych.2010.15041 · Cited by 29

A dynamic multimodal approach for assessing learners' interaction experience

Jraidi, I., Chaouachi, M., & Frasson, C. (2013) · INTERNATIONAL CONFERENCE ON MULTIMODAL INTERACTION · doi:10.1145/2522848.2522896 · Cited by 29

Automatic Behaviour Understanding in Medicine

Valstar, M. (2014) · doi:10.1145/2666253.2666260 · Cited by 29

Affective responses to system messages in human–computer-interaction: Effects of modality and message type

Pfister, H., Wollstädter, S., & Peter, C. (2011) · Interacting with Computers · doi:10.1016/j.intcom.2011.05.006 · Cited by 30

Recognition of Intensive Valence and Arousal Affective States via Facial Electromyographic Activity in Young and Senior Adults

Tan, J.-W., Andrade, A. D. O., Li, H., Walter, S., Hrabal, D., Rukavina, S., Limbrecht-Ecklundt, K., Hoffman, H., & Traue, H. C. (2016) · PLoS ONE · doi:10.1371/journal.pone.0146691 · Cited by 29

Towards Attentive, Bi-directional MOOC Learning on Mobile Devices

Xiao, X., & Wang, J. (2015) · INTERNATIONAL CONFERENCE ON MULTIMODAL INTERACTION · doi:10.1145/2818346.2820754 · Cited by 29

Modeling and adjusting in-game difficulty based on facial expression analysis

Blom, P. M., Bakkes, S. C. J., & Spronck, P. H. M. (2019) · Entertainment Computing · doi:10.1016/j.entcom.2019.100307 · Cited by 29

Unsupervised multi-modal representation learning for affective computing with multi-corpus wearable data

Ross, K., Hungler, P. C., & Etemad, A. (2021) · Journal of Ambient Intelligence and Humanized Computing · doi:10.1007/s12652-021-03462-9 · Cited by 33

AffectivelyVR: Towards VR Personalized Emotion Recognition

Gupta, K., Lazarević, J., Pai, Y. S., & Billinghurst, M. (2020) · Virtual Reality Software and Technology · doi:10.1145/3385956.3422122 · Cited by 31

MUMBAI: multi-person, multimodal board game affect and interaction analysis dataset

Doyran, M., Schimmel, A., Baki, P., Ergin, K., Türkmen, B., Salah, A. A. A., Bakkes, S. C. J., Kaya, H., Poppe, R. W., & Salah, A. A. (2021) · Journal on Multimodal User Interfaces · doi:10.1007/s12193-021-00364-0 · Cited by 32

Affective Computing for Late-Life Mood and Cognitive Disorders

Smith, E., Storch, E. A., Vahia, I. V., Wong, S. T. C., Lavretsky, H., Cummings, J. L., & Eyre, H. A. (2021) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2021.782183 · Cited by 35

Machine Learning Algorithms for Detection and Classifications of Emotions in Contact Center Applications

Płaza, M., Trusz, S., Kęczkowska, J., Boksa, E., Sadowski, S., & Koruba, Z. (2022) · Sensors · doi:10.3390/s22145311 · Cited by 29

OPO-FCM: A Computational Affection Based OCC-PAD-OCEAN Federation Cognitive Modeling Approach

Liu, F., Wang, H.-Y., Shen, S., Jia, X., Hu, J., Zhang, J., Wang, X.-Y., Lei, Y., Zhou, A., Qi, J., et al. (2022) · IEEE Transactions on Computational Social Systems · doi:10.1109/tcss.2022.3199119 · Cited by 30

Trust in Electronic Commerce

Weigand, H., & van den Heuvel, W. (2001) · Springer eBooks · doi:10.1007/978-94-017-3614-5_12 · Cited by 29

Abort, Retry, Fail: Scoping Techno-Regulation and Other Techno-Effects

van den Berg, B., & Leenes, R. E. (2013) · Ius gentium · doi:10.1007/978-94-007-6314-2_4 · Cited by 28

Extracting neurophysiological signals reflecting users’ emotional and affective responses to BCI use: A systematic literature review

Liberati, G., Federici, S., & Pasqualotto, E. (2015) · Neurorehabilitation · doi:10.3233/nre-151266 · Cited by 29

Dimensionality reduction-based spoken emotion recognition

Zhang, S., & Zhao, X. (2011) · Multimedia Tools and Applications · doi:10.1007/s11042-011-0887-x · Cited by 29

Integrating an educational 3D game in Moodle

González, C. S. G., & Blanco, F. (2007) · Simulation & Gaming · doi:10.1177/1046878108319585 · Cited by 29

EEG-based emotion recognition using discriminative graph regularized extreme learning machine

Zhu, J., Zheng, W., Peng, Y. K., Duan, R.-N., & Lu, B. (2014) · International Joint Conference on Neural Networks (IJCNN) · doi:10.1109/ijcnn.2014.6889618 · Cited by 29

Categorization and analysis of text in computer mediated communication archives using visualization

Abbasi, A., & Chen, H. (2007) · ACM/IEEE Joint Conference on Digital Libraries · doi:10.1145/1255175.1255178 · Cited by 29

Employing both gender and emotion cues to enhance speaker identification performance in emotional talking environments

Shahin, I. M. A. (2013) · International Journal of Speech Technology · doi:10.1007/s10772-013-9188-2 · Cited by 29

Multimodal approach to affective human-robot interaction design with children

Okita, S. Y., Ng‐Thow‐Hing, V., & Sarvadevabhatla, R. K. (2011) · ACM Transactions on Interactive Intelligent Systems · doi:10.1145/2030365.2030370 · Cited by 29

Computational models of emotions for autonomous agents: major challenges

Rodríguez, L.-F., & Ramos, F. (2012) · Artificial Intelligence Review · doi:10.1007/s10462-012-9380-9 · Cited by 29

A systematic review of shared visualisation to achieve common ground

Yusoff, N. M., & Salim, S. S. (2014) · Journal of Visual Languages & Computing · doi:10.1016/j.jvlc.2014.12.003 · Cited by 36

Perceptual user interfaces: affective perception

Picard, R. W. (2000) · Communications of the ACM · doi:10.1145/330534.330539 · Cited by 29

Online Multiplayer Games

Bainbridge, W. S. (2010) · Synthesis lectures on information concepts, retrieval, and services · doi:10.1007/978-3-031-02268-5 · Cited by 29

Can e-Learner's emotion be recognized from interactive Chinese texts?

Tian, F., Zheng, Q., Zhao, R., Chen, T., & Jia, X. (2009) · International Conference on Computer Supported Cooperative Work in Design (CSCWD) · doi:10.1109/cscwd.2009.4968116 · Cited by 29

Voices of Attraction

Madan, A., & Caneel, R. (2004) · Cited by 29

Towards disappearing user interfaces for ubiquitous computing: human enhancement from sixth sense to super senses

Hui, T., & Sherratt, R. S. (2016) · Journal of Ambient Intelligence and Humanized Computing · doi:10.1007/s12652-016-0409-9 · Cited by 32

Evaluating Electroencephalography Engagement Indices During Video Game Play.

McMahan, T., Parberry, I., & Parsons, T. D. (2015) · Cited by 29

Automatic Generation of Music for Inducing Emotive Response

Monteith, K., Martinez, T. R., & Ventura, D. A. (2010) · Cited by 29

Multi-modal emotive computing in a smart house environment

Moncrieff, S., Venkatesh, S., WEST, G. A. W., & Greenhill, S. (2006) · Pervasive and Mobile Computing · doi:10.1016/j.pmcj.2006.07.003 · Cited by 30

The social body in motion: cognitive development in infants and androids

Lindblom, J., & Tom Ziemke, B. (2006) · Connection Science · doi:10.1080/09540090600868888 · Cited by 29

Extracting Moods from Pictures and Sounds

Hanjalić, A. (2006) · Cited by 29

Multimodal Integration - A Biological View

Coen, M. H. (2001) · Cited by 29

Fuzzy emotion recognition in natural speech dialogue

Austermann, A., Esau, N., Kleinjohann, L., & Kleinjohann, B. (2006) · IEEE RO-MAN · doi:10.1109/roman.2005.1513798 · Cited by 29

Robust face detection against brightness fluctuation and size variation

Hidai, K., Mizoguchi, H., Hiraoka, K., Tanaka, M., Shigehara, T., & Mishima, T. (2002) · IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · doi:10.1109/iros.2000.893213 · Cited by 29

Visual Affect Around the World: A Large-scale Multilingual Visual Sentiment OntologyPreprint

Jou, B., Chen, T., Pappas, N., Реди, М., Topkara, M., & Chang, S. (2015) · arXiv (Cornell University) · doi:10.48550/arxiv.1508.03868 · Cited by 29

Cross-Modal Guiding Neural Network for Multimodal Emotion Recognition From EEG and Eye Movement Signals

Fu, B., Chu, W., Gu, C., & Liu, Y. (2024) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2024.3419043 · Cited by 28

Study on Speech Emotion Recognition System in E-Learning

Aiqin, Z., & Luo, Q. (2007) · Lecture notes in computer science · doi:10.1007/978-3-540-73110-8_59 · Cited by 28

Using unlabeled data to improve classification of emotional states in human computer interaction

Schels, M., Kächele, M., Glodek, M., Hrabal, D., Walter, S., & Schwenker, F. (2013) · Journal on Multimodal User Interfaces · doi:10.1007/s12193-013-0133-0 · Cited by 29

EGO: A personalized multimedia management and retrieval tool

Urban, J., & Jose, J. M. (2006) · International Journal of Intelligent Systems · doi:10.1002/int.20157 · Cited by 28

Emotion recognition based on a novel triangular facial feature extraction method

Huang, K., Huang, S., & Kuo, Y.-H. (2010) · International Joint Conference on Neural Networks (IJCNN) · doi:10.1109/ijcnn.2010.5596374 · Cited by 28

Facial Expression Recognition in the Presence of Speech Using Blind Lexical Compensation

Mariooryad, S., & Busso, C. (2015) · IEEE Transactions on Affective Computing · doi:10.1109/taffc.2015.2490070 · Cited by 28

Smartphone accelerometer data used for detecting human emotions

Olsen, A. F., & Tørresen, J. (2016) · International Conference on Systems and Informatics (ICSAI) · doi:10.1109/icsai.2016.7810990 · Cited by 28

Emotional affordances in human-machine interactive planning and negotiation

Franzoni, V., Milani, A., & Vallverdú, J. (2017) · IEEE/WIC/ACM International Conference on Web Intelligence · doi:10.1145/3106426.3109421 · Cited by 28

Detection and computational analysis of psychological signals using a virtual human interviewing agent

Rizzo, A., Scherer, S. J., DeVault, D., Gratch, J. S., Artstein, R., Hartholt, A., Lucas, G., Marsella, S., Morbini, F., Nazarian, A., et al. (2014) · ENLIGHTEN (Jurnal Bimbingan dan Konseling Islam) · Cited by 28

Re-defining the Role of Artificial Intelligence (AI) in Wiser Service Systems

Barile, S., Piciocchi, P., Bassano, C., Spohrer, J., & Pietronudo, M. (2018) · Advances in Intelligent Systems and Computing · doi:10.1007/978-3-319-94229-2_16 · Cited by 24

Affect Recognition in Code Review: An In-situ Biometric Study of Reviewer’s Affect

Vrzáková, H., Begel, A., Mehtätalo, L., & Bednarik, R. (2019) · Journal of Systems and Software · doi:10.1016/j.jss.2019.110434 · Cited by 31

Exploring EEG microstates for affective computing: decoding valence and arousal experiences during video watching

Shen, X., Hu, X., Liu, S., Song, S., & Zhang, D. (2020) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc44109.2020.9175482 · Cited by 28

Domain Adaptation for Cross-Subject Emotion Recognition by Subject Clustering

Liu, J., Shen, X., Song, S., & Zhang, D. (2021) · International IEEE/EMBS Conference on Neural Engineering · doi:10.1109/ner49283.2021.9441368 · Cited by 28

Separable convolutional neural networks for facial expressions recognition

Chowanda, A. (2021) · Journal Of Big Data · doi:10.1186/s40537-021-00522-x · Cited by 29

PREREQUISITES FOR AFFECTIVE SIGNAL PROCESSING (ASP)

van den Broek, E. L., Janssen, J. H., Westerink, J. H. D. M., & Healey, J. (2009) · International Conference on Bio-inspired Systems and Signal Processing · doi:10.5220/0001780504260433 · Cited by 29

Studying and enhancing talking condition recognition in stressful and emotional talking environments based on HMMs, CHMM2s and SPHMMs

Shahin, I. M. A. (2011) · Journal on Multimodal User Interfaces · doi:10.1007/s12193-011-0082-4 · Cited by 28

Is happy better than sad even if they are both non-adaptive? Effects of emotional expressions of talking-head interface agents

Gong, L. (2006) · International Journal of Human-Computer Studies · doi:10.1016/j.ijhcs.2006.09.005 · Cited by 28

Modelling affect expression and recognition in an interactive learning environment

McQuiggan, S. W., & Lester, J. C. (2009) · International Journal of Learning Technology · doi:10.1504/ijlt.2009.028807 · Cited by 28

Ontology Based Affective Context Representation

Benţa, K., Rarău, A., & Cremene, M. (2007) · Euro American Conference on Telematics and Information Systems · doi:10.1145/1352694.1352741 · Cited by 28

e‐Learning as energetic learning

Bennet, A., & Bennet, D. (2008) · VINE · doi:10.1108/03055720810889842 · Cited by 28

Real time emotion aware applications: A case study employing emotion evocative pictures and neuro-physiological sensing enhanced by Graphic Processor Units

Konstantinidis, E. I., Frantzidis, C. A., Pappas, C., & Bamidis, P. D. (2012) · Computer Methods and Programs in Biomedicine · doi:10.1016/j.cmpb.2012.03.008 · Cited by 28

PAD-based multimodal affective fusion

Gilroy, S. W., Cavazza, M., Niiranen, M., André, E., Vogt, T., Urbain, J., Benayoun, M., Seichter, H., & Billinghurst, M. (2009) · International Conference on Affective Computing and Intelligent Interaction and workshops · doi:10.1109/acii.2009.5349552 · Cited by 28

Facial emotion recognition in modern distant education system using SVM

Sun, J.-M., Pei, X.-S., & Zhou, S.-S. (2008) · 2008 International Conference on Machine Learning and Cybernetics · doi:10.1109/icmlc.2008.4621018 · Cited by 28

Multimodal Emotion Recognition from Low-Level Cues

Pantić, M., Caridakis, G., André, E., Kim, J., Karpouzis, K. C., & Kollias, S. (2010) · Cognitive technologies · doi:10.1007/978-3-642-15184-2_8 · Cited by 28

Towards Emotion Recognition in Human Computer Interaction

Palm, G., & Glodek, M. (2012) · Smart innovation, systems and technologies · doi:10.1007/978-3-642-35467-0_32 · Cited by 28

Improving Medical Students’ Awareness of Their Non-Verbal Communication through Automated Non-Verbal Behavior Feedback

Liu, C., Calvo, R. A., & Lim, R. (2016) · Frontiers in ICT · doi:10.3389/fict.2016.00011 · Cited by 29

Designer Modeling for Personalized Game Content Creation Tools

Liapis, A., Yannakakis, G. N., & Togelius, J. (2013) · Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment · doi:10.1609/aiide.v9i2.12587 · Cited by 28

Affective level design for a role-playing videogame evaluated by a brain–computer interface and machine learning methods

Balducci, F., Grana, C., & Cucchiara, R. (2016) · The Visual Computer · doi:10.1007/s00371-016-1320-2 · Cited by 28

A cognitive-affective architecture for ECAs

Pérez, J., Cerezo, E., Arbeloa, F. J. S., & Rodríguez, L.-F. (2016) · Biologically Inspired Cognitive Architectures · doi:10.1016/j.bica.2016.10.002 · Cited by 28

Real-time emotional state detection from facial expression on embedded devices

Turabzadeh, S., Meng, H., Swash, M. R., Pleva, M., & Juhár, J. (2017) · International Conference on Innovative Computing Technology · doi:10.1109/intech.2017.8102423 · Cited by 28

Affective brain-computer interfaces: Choosing a meaningful performance measuring metric

Mowla, M. R., Cano, R. I., Dhuyvetter, K. J., & Thompson, D. E. (2020) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2020.104001 · Cited by 28

Socially Intelligent Agents in Educational Games

Conati, C., & Klawe, M. M. (2006) · Kluwer Academic Publishers eBooks · doi:10.1007/0-306-47373-9_26 · Cited by 28

Acoustic Emotion Recognition for Affective Computer Gaming

Jones, C. M., & Sutherland, J. (2008) · Lecture notes in computer science · doi:10.1007/978-3-540-85099-1_18 · Cited by 28

Personifying the e-Market: A Framework for Social Agents.

Angeli, A. D., Lynch, P., & Johnson, G. I. (2001) · Iris (University of Trento) · Cited by 28

Exploiting a Vowel Based Approach for Acted Emotion Recognition

Ringeval, F., & Chétouani, M. (2008) · Lecture notes in computer science · doi:10.1007/978-3-540-70872-8_19 · Cited by 28

Making Intelligent Tutoring Systems Culturally-Aware: The use of Hofstede's Cultural Dimensions

Blanchard, E., & Frasson, C. (2005) · HAL · Cited by 28

Review of Affective Computing

Sloman, A. (1999) · doi:10.1609/aimag.v20i1.1448 · Cited by 44

Giving Computers Emotions-Why and How

Fulda, J. S. (1998) · ACM SIGCAS Computers and Society · doi:10.1145/308364.606115 · Cited by 1

Affect and Emotion in Human-Computer Interaction

Hutchison, D., Weikum, G., Vardi, M. Y., Tygar, D., Terzopoulos, D., Sudan, M., Steffen, B., Peter, C., Pandu Rangan, C., Nierstrasz, O., et al. (2008) · Lecture notes in computer science · doi:10.1007/978-3-540-85099-1 · Cited by 186

Emotion‐Oriented Systems

(2013) · Wiley eBooks · doi:10.1002/9781118601938 · Cited by 10

“Affective Computing” Is Not an Oxymoron

Picard, R. W., & Plasencia, A. (2017) · The MIT Press eBooks · doi:10.7551/mitpress/9780262036016.003.0023