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emotion recognition
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computer mediated communication
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behavioural sciences computing
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1404
computer games
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human computer interaction
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behavioural sciences computing
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behavioural sciences computing
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behavioural sciences
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1512
Bayes methods
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1410
body sensor networks
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1410
intelligent transportation systems
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1411
computational linguistics
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correlation methods
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1411
emotion recognition
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1411
audio signal processing
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1412
electroencephalography
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1412
body area networks
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1412
behavioural sciences computing
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behavioural sciences computing
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convolution
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1905
emotion recognition, learning (artificial intelligence),
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dynamic learning
BibRef
Zhang, Z.X.[Zi-Xing],
Coutinho, E.[Eduardo],
Deng, J.[Jun],
Schuller, B.[Björn],
Distributing Recognition in Computational Paralinguistics,
AffCom(5), No. 4, October 2014, pp. 406-417.
IEEE DOI
1503
client-server systems
BibRef
Wang, K.X.[Kun-Xia],
An, N.[Ning],
Li, B.N.[Bing Nan],
Zhang, Y.Y.[Yan-Yong],
Li, L.[Lian],
Speech Emotion Recognition Using Fourier Parameters,
AffCom(6), No. 1, January 2015, pp. 69-75.
IEEE DOI
1506
Fourier analysis
BibRef
Fairhurst, M.,
Erbilek, M.,
Li, C.[Cheng],
Study of automatic prediction of emotion from handwriting samples,
IET-Bio(4), No. 2, 2015, pp. 90-97.
DOI Link
1507
digital forensics
BibRef
Gunes, H.[Hatice],
Hung, H.[Hayley],
Emotional and Social Signals:
A Neglected Frontier in Multimedia Computing?,
MultMedMag(22), No. 2, April 2015, pp. 76-85.
IEEE DOI
1507
affective signals
BibRef
Turchet, L.,
Bresin, R.,
Effects of Interactive Sonification on Emotionally Expressive Walking
Styles,
AffCom(6), No. 2, April 2015, pp. 152-164.
IEEE DOI
1507
acoustic signal processing
BibRef
Turchet, L.,
Rodà, A.,
Emotion Rendering in Auditory Simulations of Imagined Walking Styles,
AffCom(8), No. 2, April 2017, pp. 241-253.
IEEE DOI
1706
Context, Emotion recognition, Engines, Footwear, Legged locomotion,
Music, Production, Emotion rendering, footstep sounds, walking
BibRef
Turchet, L.,
Zanotto, D.,
Minto, S.,
Rodà, A.,
Agrawal, S.K.,
Emotion Rendering in Plantar Vibro-Tactile Simulations of Imagined
Walking Styles,
AffCom(8), No. 3, July 2017, pp. 340-354.
IEEE DOI
1709
Engines, Foot, Footwear, Haptic interfaces, Legged locomotion,
Rendering (computer graphics), Vibrations, Emotion rendering,
SoleSounds, footstep sounds, walking
BibRef
Hariharan, A.,
Adam, M.T.P.,
Blended Emotion Detection for Decision Support,
HMS(45), No. 4, August 2015, pp. 510-517.
IEEE DOI
1506
Accuracy
BibRef
Mone, G.[Gregory],
Sensing Emotions,
CACM(59), No. 9, September 2015, pp. 15-16.
DOI Link
1509
News story on affective computing.
BibRef
Wang, X.,
Jia, J.,
Tang, J.,
Wu, B.,
Cai, L.,
Xie, L.,
Modeling Emotion Influence in Image Social Networks,
AffCom(6), No. 3, July 2015, pp. 286-297.
IEEE DOI
1509
Analytical models
BibRef
Liang, R.[Ruiyu],
Tao, H.[Huawei],
Tang, G.C.[Gui-Chen],
Wang, Q.Y.[Qing-Yun],
Zhao, L.[Li],
A Salient Feature Extraction Algorithm for Speech Emotion Recognition,
IEICE(E98-D), No. 9, September 2015, pp. 1715-1718.
WWW Link.
1509
BibRef
Trentin, E.[Edmondo],
Scherer, S.[Stefan],
Schwenker, F.[Friedhelm],
Emotion recognition from speech signals via a probabilistic
echo-state network,
PRL(66), No. 1, 2015, pp. 4-12.
Elsevier DOI
1511
Emotion recognition
BibRef
Kachele, M.[Markus],
Zharkov, D.[Dimitrij],
Meudt, S.[Sascha],
Schwenker, F.[Friedhelm],
Prosodic, Spectral and Voice Quality Feature Selection Using a
Long-Term Stopping Criterion for Audio-Based Emotion Recognition,
ICPR14(803-808)
IEEE DOI
1412
Accuracy
BibRef
Nardelli, M.,
Valenza, G.,
Greco, A.,
Lanata, A.,
Scilingo, E.P.,
Recognizing Emotions Induced by Affective Sounds through Heart Rate
Variability,
AffCom(6), No. 4, October 2015, pp. 385-394.
IEEE DOI
1512
Acoustics
BibRef
Wang, S.,
Wang, J.,
Wang, Z.,
Ji, Q.,
Multiple Emotion Tagging for Multimedia Data by Exploiting High-Order
Dependencies Among Emotions,
MultMed(17), No. 12, December 2015, pp. 2185-2197.
IEEE DOI
1512
Databases
BibRef
Kim, J.C.,
Clements, M.A.,
Multimodal Affect Classification at Various Temporal Lengths,
AffCom(6), No. 4, October 2015, pp. 371-384.
IEEE DOI
1512
Audio-visual systems
BibRef
Hoey, J.[Jesse],
Schröder, T.[Tobias],
Alhothali, A.[Areej],
Affect control processes: Intelligent affective interaction using a
partially observable Markov decision process,
AI(230), No. 1, 2016, pp. 134-172.
Elsevier DOI
1512
Affect
BibRef
Rao, Y.H.[Yang-Hui],
Contextual Sentiment Topic Model for Adaptive Social Emotion
Classification,
IEEE_Int_Sys(31), No. 1, January 2016, pp. 41-47.
IEEE DOI
1602
emotion recognition
BibRef
Liu, K.,
Tolins, J.,
Fox Tree, J.E.,
Neff, M.,
Walker, M.A.,
Two Techniques for Assessing Virtual Agent Personality,
AffCom(7), No. 1, January 2016, pp. 94-105.
IEEE DOI
1603
Electronic mail
BibRef
Cambria, E.,
Affective Computing and Sentiment Analysis,
IEEE_Int_Sys(31), No. 2, March 2016, pp. 102-107.
IEEE DOI
1604
Affective computing
BibRef
Zong, Y.,
Zheng, W.,
Zhang, T.,
Huang, X.,
Cross-Corpus Speech Emotion Recognition Based on Domain-Adaptive
Least-Squares Regression,
SPLetters(23), No. 5, May 2016, pp. 585-589.
IEEE DOI
1604
emotion recognition
BibRef
Yan, J.,
Zheng, W.,
Xu, Q.,
Lu, G.,
Li, H.,
Wang, B.,
Sparse Kernel Reduced-Rank Regression for Bimodal Emotion Recognition
From Facial Expression and Speech,
MultMed(18), No. 7, July 2016, pp. 1319-1329.
IEEE DOI
1608
emotion recognition
BibRef
Tao, H.[Huawei],
Liang, R.[Ruiyu],
Zha, C.[Cheng],
Zhang, X.[Xinran],
Zhao, L.[Li],
Spectral Features Based on Local Hu Moments of Gabor Spectrograms for
Speech Emotion Recognition,
IEICE(E99-D), No. 8, August 2016, pp. 2186-2189.
WWW Link.
1608
BibRef
Zhalehpour, S.[Sara],
Akhtar, Z.[Zahid],
Erdem, C.E.[Cigdem Eroglu],
Multimodal emotion recognition based on peak frame selection from video,
SIViP(10), No. 5, May 2016, pp. 827-834.
WWW Link.
1608
BibRef
Gong, J.,
Asare, P.,
Qi, Y.,
Lach, J.,
Piecewise Linear Dynamical Model for Action Clustering from
Real-World Deployments of Inertial Body Sensors,
AffCom(7), No. 3, July 2016, pp. 231-242.
IEEE DOI
1609
Emotion recognition
BibRef
Wen, H.W.[Hong-Wei],
Liu, Y.[Yue],
Rekik, I.[Islem],
Wang, S.P.[Sheng-Pei],
Chen, Z.Q.[Zhi-Qiang],
Zhang, J.S.[Ji-Shui],
Zhang, Y.[Yue],
Peng, Y.[Yun],
He, H.G.[Hui-Guang],
Multi-modal multiple kernel learning for accurate identification of
Tourette syndrome children,
PR(63), No. 1, 2017, pp. 601-611.
Elsevier DOI
1612
Tourette syndrome
BibRef
Bandhakavi, A.[Anil],
Wiratunga, N.[Nirmalie],
Massie, S.[Stewart],
Padmanabhan, D.[Deepak],
Lexicon Generation for Emotion Detection from Text,
IEEE_Int_Sys(32), No. 1, January 2017, pp. 102-108.
IEEE DOI
1702
Emotion recognition
BibRef
Bandhakavi, A.[Anil],
Wiratunga, N.[Nirmalie],
Padmanabhan, D.[Deepak],
Massie, S.[Stewart],
Lexicon based feature extraction for emotion text classification,
PRL(93), No. 1, 2017, pp. 133-142.
Elsevier DOI
1706
Emotion, classification
BibRef
Albornoz, E.M.,
Milone, D.H.,
Emotion recognition in never-seen languages using a novel ensemble
method with emotion profiles,
AffCom(8), No. 1, January 2017, pp. 43-53.
IEEE DOI
1703
Cultural differences
BibRef
Likforman-Sulem, L.,
Esposito, A.,
Faundez-Zanuy, M.,
Clémençon, S.,
Cordasco, G.,
EMOTHAW: A Novel Database for Emotional State Recognition From
Handwriting and Drawing,
HMS(47), No. 2, April 2017, pp. 273-284.
IEEE DOI
1704
Atmospheric measurements
BibRef
Stratou, G.[Giota],
Morency, L.P.[Louis-Philippe],
MultiSense: Context-Aware Nonverbal Behavior Analysis Framework:
A Psychological Distress Use Case,
AffCom(8), No. 2, April 2017, pp. 190-203.
IEEE DOI
1706
Affective computing, Computer architecture, Context, Pipelines,
Psychology, Real-time systems, Synchronization, MultiSense,
automatic distress assessment, behavior quantification,
framework for multimodal behavioral understanding, system, for,
affective, computing
BibRef
Venek, V.[Verena],
Scherer, S.[Stefan],
Morency, L.P.[Louis-Philippe],
Rizzo, A.S.[Albert Skip],
Pestian, J.[John],
Adolescent Suicidal Risk Assessment in Clinician-Patient Interaction,
AffCom(8), No. 2, April 2017, pp. 204-215.
IEEE DOI
1706
Feature extraction, Interviews, Pediatrics, Repeaters,
Risk management, Speech, Support vector machines,
Behavior analytics, clinician-patient interaction,
hierarchical classifiers, ubiquitous questions, youth, suicide
BibRef
Kim, M.,
Doh, Y.Y.,
Computational Modeling of Players: Emotional Response Patterns to the
Story Events of Video Games,
AffCom(8), No. 2, April 2017, pp. 216-227.
IEEE DOI
1706
Analytical models, Computational modeling, Games, Investment,
Mathematical model, Media, Predictive models,
Computational emotion model, player experience, player modeling,
video, game, narrative
BibRef
Palo, H.K.[Hemanta Kumar],
Chandra, M.[Mahesh],
Mohanty, M.N.[Mihir Narayan],
Emotion recognition using MLP and GMM for Oriya language,
IJCVR(7), No. 4, 2017, pp. 426-442.
DOI Link
1708
BibRef
Goshvarpour, A.[Ateke],
Daneshvar, S.[Sabalan],
Discrimination between different emotional states based on the chaotic
behavior of galvanic skin responses,
SIViP(11), No. 7, October 2017, pp. 1347-1355.
Springer DOI
1708
BibRef
Guendil, Z.[Zied],
Lachiri, Z.[Zied],
Maaoui, C.[Choubeila],
Computational framework for emotional VAD prediction using regularized
Extreme Learning Machine,
MultInfoRetr(6), No. 3, September 2017, pp. 251-261.
Springer DOI
1708
BibRef
Mariooryad, S.[Soroosh],
Busso, C.[Carlos],
Facial Expression Recognition in the Presence of Speech Using Blind
Lexical Compensation,
AffCom(7), No. 4, October 2016, pp. 346-359.
IEEE DOI
1612
BibRef
Earlier:
Feature and model level compensation of lexical content for facial
emotion recognition,
FG13(1-6)
IEEE DOI
1309
BibRef
Earlier:
Factorizing speaker, lexical and emotional variabilities observed in
facial expressions,
ICIP12(2605-2608).
IEEE DOI
1302
compensation
Bilinear models
BibRef
Mariooryad, S.[Soroosh],
Busso, C.[Carlos],
Exploring Cross-Modality Affective Reactions for Audiovisual Emotion
Recognition,
AffCom(4), No. 2, 2013, pp. 183-196.
IEEE DOI
1307
Entrainment
BibRef
Mariooryad, S.,
Busso, C.,
Correcting Time-Continuous Emotional Labels by Modeling the Reaction
Lag of Evaluators,
AffCom(6), No. 2, April 2015, pp. 97-108.
IEEE DOI
1507
emotion recognition
BibRef
Busso, C.,
Mariooryad, S.,
Metallinou, A.,
Narayanan, S.,
Iterative Feature Normalization Scheme for Automatic Emotion
Detection from Speech,
AffCom(4), No. 4, October 2013, pp. 386-397.
IEEE DOI
1406
emotion recognition
BibRef
Deng, J.,
Zhang, Z.,
Eyben, F.,
Schuller, B.,
Autoencoder-based Unsupervised Domain Adaptation for Speech Emotion
Recognition,
SPLetters(21), No. 9, Sept 2014, pp. 1068-1072.
IEEE DOI
1406
Emotion recognition
BibRef
Deng, J.,
Xu, X.,
Zhang, Z.,
Frühholz, S.,
Schuller, B.,
Universum Autoencoder-Based Domain Adaptation for Speech Emotion
Recognition,
SPLetters(24), No. 4, April 2017, pp. 500-504.
IEEE DOI
1704
Databases
BibRef
Mencattini, A.,
Martinelli, E.,
Ringeval, F.,
Schuller, B.,
Natale, C.D.,
Continuous Estimation of Emotions in Speech by Dynamic Cooperative
Speaker Models,
AffCom(8), No. 3, July 2017, pp. 314-327.
IEEE DOI
1709
Data models, Databases, Emotion recognition, Gold, Predictive models,
Speech, Standards, Speech emotion recognition,
cooperative regression model, naturalistic emotional display
BibRef
Naji, M.[Mohsen],
Firoozabadi, M.[Mohammd],
Azadfallah, P.[Parviz],
Emotion classification during music listening from forehead biosignals,
SIViP(9), No. 6, September 2015, pp. 1365-1375.
WWW Link.
1509
BibRef
Savran, A.,
Cao, H.[Houwei],
Nenkova, A.,
Verma, R.,
Temporal Bayesian Fusion for Affect Sensing:
Combining Video, Audio, and Lexical Modalities,
Cyber(45), No. 9, September 2015, pp. 1927-1941.
IEEE DOI
1509
Bayes methods
BibRef
Zhao, R.,
Mao, K.,
Cyberbullying Detection Based on Semantic-Enhanced Marginalized
Denoising Auto-Encoder,
AffCom(8), No. 3, July 2017, pp. 328-339.
IEEE DOI
1709
Analytical models, Feature extraction, Media, Noise reduction,
Numerical models, Robustness, Semantics, Cyberbullying detection,
representation learning, stacked denoising autoencoders,
text mining, word, embedding
BibRef
Georgakis, C.[Christos],
Panagakis, Y.[Yannis],
Zafeiriou, S.P.[Stefanos P.],
Pantic, M.[Maja],
The Conflict Escalation Resolution (CONFER) Database,
IVC(65), No. 1, 2017, pp. 37-48.
Elsevier DOI
1709
BibRef
Earlier: A2, A3, A4, Only:
Audiovisual Conflict Detection in Political Debates,
FacBeh14(306-314).
Springer DOI
1504
Automatic conflict analysis
BibRef
Fortin, P.E.,
Cooperstock, J.R.,
Laughter and Tickles: Toward Novel Approaches for Emotion and
Behavior Elicitation,
AffCom(8), No. 4, October 2017, pp. 508-521.
IEEE DOI
1712
Auditory system, Haptic interfaces, Physiology, Psychology,
Temperature sensors, Vibrations, Visualization, Laughter,
tickling
BibRef
Li, M.,
Lu, Q.,
Long, Y.,
Gui, L.,
Inferring Affective Meanings of Words from Word Embedding,
AffCom(8), No. 4, October 2017, pp. 443-456.
IEEE DOI
1712
Affective computing, Computational modeling, Context,
Crowdsourcing, Knowledge based systems, Manuals, Semantics,
word embedding
BibRef
Cambria, E.,
Hussain, A.,
Vinciarelli, A.,
Affective Reasoning for Big Social Data Analysis,
AffCom(8), No. 4, October 2017, pp. 426-427.
IEEE DOI
1712
BibRef
Zhang, S.Q.[Shi-Qing],
Zhang, S.L.[Shi-Liang],
Huang, T.J.[Tie-Jun],
Gao, W.[Wen],
Speech Emotion Recognition Using Deep Convolutional Neural Network
and Discriminant Temporal Pyramid Matching,
MultMed(20), No. 6, June 2018, pp. 1576-1590.
IEEE DOI
1805
Acoustics, Convolution, Emotion recognition, Feature extraction,
Neural networks, Speech, Speech recognition, Lp-norm pooling,
feature learning
BibRef
Shepstone, S.E.,
Tan, Z.H.,
Jensen, S.H.,
Audio-Based Granularity-Adapted Emotion Classification,
AffCom(9), No. 2, April 2018, pp. 176-190.
IEEE DOI
1806
Context, Emotion recognition, Facsimile, Motion pictures, Speech,
Support vector machines, Visualization, Emotion, SVM, affect,
multidimensional scaling
BibRef
Sahoo, S.,
Routray, A.,
Detecting Aggression in Voice Using Inverse Filtered Speech Features,
AffCom(9), No. 2, April 2018, pp. 217-226.
IEEE DOI
1806
Cameras, Feature extraction, Interviews, Psychology, Speech,
Speech processing, TV, Aggression detection,
speech inverse filtering
BibRef
Zhao, M.M.[Ming-Min],
Adib, F.[Fadel],
Katabi, D.[Dina],
Emotion Recognition Using Wireless Signals,
CACM(61), No. 9, September 2018, pp. 91-100.
DOI Link
1809
From RF signals reflected of the body. From detecting heartbeats.
BibRef
Chen, M.Y.[Ming-Yi],
He, X.J.[Xuan-Ji],
Yang, J.[Jing],
Zhang, H.[Han],
3-D Convolutional Recurrent Neural Networks With Attention Model for
Speech Emotion Recognition,
SPLetters(25), No. 10, October 2018, pp. 1440-1444.
IEEE DOI
1810
convolution, emotion recognition, feature extraction,
feedforward neural nets, recurrent neural nets,
speech emotion recognition (SER)
BibRef
Zhang, S.,
Zhang, S.,
Huang, T.,
Gao, W.,
Tian, Q.,
Learning Affective Features With a Hybrid Deep Model for Audio-Visual
Emotion Recognition,
CirSysVideo(28), No. 10, October 2018, pp. 3030-3043.
IEEE DOI
1811
Feature extraction, Emotion recognition, Visualization,
Image segmentation, Machine learning, Databases, Convolution,
multimodality fusion
BibRef
Rzeszewski, M.[Michal],
Luczys, P.[Piotr],
Care, Indifference and Anxiety:
Attitudes toward Location Data in Everyday Life,
IJGI(7), No. 10, 2018, pp. xx-yy.
DOI Link
1811
BibRef
Liu, Y.,
Yu, M.,
Zhao, G.,
Song, J.,
Ge, Y.,
Shi, Y.,
Real-Time Movie-Induced Discrete Emotion Recognition from EEG Signals,
AffCom(9), No. 4, October 2018, pp. 550-562.
IEEE DOI
1812
Emotion recognition, Real-time systems, Electroencephalography,
Brain models, Films, Support vector machines, Affective computing,
movie
BibRef
Belkaid, M.,
Cuperlier, N.,
Gaussier, P.,
Autonomous Cognitive Robots Need Emotional Modulations:
Introducing the eMODUL Model,
SMCS(49), No. 1, January 2019, pp. 206-215.
IEEE DOI
1901
Cognition, Robots, Appraisal, Task analysis, Modulation,
Computational modeling, Psychology, Emotional modulations,
robot emotions
BibRef
Jing, S.L.[Shao-Ling],
Mao, X.[Xia],
Chen, L.J.[Li-Jiang],
Automatic speech discrete labels to dimensional emotional values
conversion method,
IET-Bio(8), No. 2, March 2019, pp. 168-176.
DOI Link
1902
BibRef
Xu, X.,
Deng, J.,
Coutinho, E.,
Wu, C.,
Zhao, L.,
Schuller, B.W.,
Connecting Subspace Learning and Extreme Learning Machine in Speech
Emotion Recognition,
MultMed(21), No. 3, March 2019, pp. 795-808.
IEEE DOI
1903
emotion recognition, feedforward neural nets, graph theory,
human computer interaction, regression analysis,
spectral regression
BibRef
Ye, J.,
Li, J.,
Newman, M.G.,
Adams, R.B.,
Wang, J.Z.,
Probabilistic Multigraph Modeling for Improving the Quality of
Crowdsourced Affective Data,
AffCom(10), No. 1, January 2019, pp. 115-128.
IEEE DOI
1903
Reliability, Data models, Probabilistic logic,
Computational modeling, Psychology, Crowdsourcing,
visual stimuli
BibRef
Li, X.,
Peng, Q.,
Sun, Z.,
Chai, L.,
Wang, Y.,
Predicting Social Emotions from Readers' Perspective,
AffCom(10), No. 2, April 2019, pp. 255-264.
IEEE DOI
1906
Statistical analysis, Predictive models, Feature extraction,
Social network services, Semantics, Internet,
complex network
BibRef
Song, P.,
Transfer Linear Subspace Learning for Cross-Corpus Speech Emotion
Recognition,
AffCom(10), No. 2, April 2019, pp. 265-275.
IEEE DOI
1906
Speech, Speech recognition, Emotion recognition, Training, Testing,
Principal component analysis, Algorithm design and analysis,
dimensionality reduction
BibRef
Jia, J.[Jia],
Zhou, S.P.[Su-Ping],
Yin, Y.F.[Yu-Feng],
Wu, B.[Boya],
Chen, W.[Wei],
Meng, F.[Fanbo],
Wang, Y.F.[Yan-Feng],
Inferring Emotions From Large-Scale Internet Voice Data,
MultMed(21), No. 7, July 2019, pp. 1853-1866.
IEEE DOI
1906
Feature extraction, Speech recognition, Emotion recognition,
Acoustics, Hidden Markov models, Neural networks,
long short-term memory
BibRef
Ren, Z.[Zhu],
Jia, J.[Jia],
Cai, L.H.[Lian-Hong],
Zhang, K.[Kuo],
Tang, J.[Jie],
Learning to Infer Public Emotions from Large-Scale Networked Voice Data,
MMMod14(I: 327-339).
Springer DOI
1405
BibRef
Avots, E.[Egils],
Sapinski, T.[Tomasz],
Bachmann, M.[Maie],
Kaminska, D.[Dorota],
Audiovisual emotion recognition in wild,
MVA(30), No. 5, July 2019, pp. 975-985.
Springer DOI
1907
BibRef
Xie, Y.[Yue],
Liang, R.[Ruiyu],
Liang, Z.L.[Zhen-Lin],
Zhao, L.[Li],
Attention-Based Dense LSTM for Speech Emotion Recognition,
IEICE(E102-D), No. 7, July 2019, pp. 1426-1429.
WWW Link.
1907
BibRef
Alarcão, S.M.,
Fonseca, M.J.,
Emotions Recognition Using EEG Signals: A Survey,
AffCom(10), No. 3, July 2019, pp. 374-393.
IEEE DOI
1909
Electroencephalography, Electrodes, Electric potential,
Emotion recognition, Feature extraction, Brain, recognition
BibRef
Zheng, W.,
Zhu, J.,
Lu, B.,
Identifying Stable Patterns over Time for Emotion Recognition from
EEG,
AffCom(10), No. 3, July 2019, pp. 417-429.
IEEE DOI
1909
Electroencephalography, Emotion recognition, Stability analysis,
Feature extraction, Brain modeling, Time-frequency analysis,
extreme learning machine
BibRef
Nguyen, T.,
Zhou, T.,
Potter, T.,
Zou, L.,
Zhang, Y.,
The Cortical Network of Emotion Regulation:
Insights From Advanced EEG-fMRI Integration Analysis,
MedImg(38), No. 10, October 2019, pp. 2423-2433.
IEEE DOI
1910
Functional magnetic resonance imaging, Electroencephalography,
Spatiotemporal phenomena, Image reconstruction, Brain modeling,
causal brain network
BibRef
Bang, E.[Eun_Seo],
Yildirim, C.[Caglar],
Virtually Empathetic?: Examining the Effects of Virtual Reality
Storytelling on Empathy,
VAMR18(I: 290-298).
Springer DOI
1807
BibRef
Drnec, K.[Kim],
Gremillion, G.[Greg],
Donavanik, D.[Daniel],
Canady, J.D.[Jonroy D.],
Atwater, C.[Corey],
Carter, E.[Evan],
Haynes, B.A.[Ben A.],
Marathe, A.R.[Amar R.],
Metcalfe, J.S.[Jason S.],
The Role of Psychophysiological Measures as Implicit Communication
Within Mixed-Initiative Teams,
VAMR18(I: 299-313).
Springer DOI
1807
BibRef
Gong, J.T.[Jiang-Tao],
Shi, Y.[Yin],
Wang, J.[Jue],
Shi, D.[Danqing],
Xu, Y.Q.[Ying-Qing],
Escape from the Dark Jungle: A 3D Audio Game for Emotion Regulation,
VAMR18(II: 57-76).
Springer DOI
1807
BibRef
de la Pava, I.[Iván],
Álvarez-Meza, A.[Andres],
Orozco, A.A.[Alvaro-Angel],
Emotion Assessment by Variability-Based Ranking of Coherence Features
from EEG,
CIARP17(203-211).
Springer DOI
1802
BibRef
Wang, F.[Fang],
Zhong, S.H.[Sheng-Hua],
Peng, J.F.[Jian-Feng],
Jiang, J.M.[Jian-Min],
Liu, Y.[Yan],
Data Augmentation for EEG-Based Emotion Recognition with Deep
Convolutional Neural Networks,
MMMod18(II:82-93).
Springer DOI
1802
BibRef
Samanta, P.[Pallabi],
Bhattacharya, D.[Diptendu],
De, A.[Amiyangshu],
Ghosh, L.[Lidia],
Konar, A.[Amit],
Music-Induced Emotion Classification from the Prefrontal Hemodynamics,
PReMI17(289-295).
Springer DOI
1711
BibRef
Sharma, S.[Shikhar],
Kumar, P.[Piyush],
Kumar, K.[Krishan],
LEXER: LEXicon Based Emotion AnalyzeR,
PReMI17(373-379).
Springer DOI
1711
BibRef
Dey, A.[Atanu],
Jenamani, M.[Mamata],
Thakkar, J.J.[Jitesh J.],
Lexical TF-IDF: An n-gram Feature Space for
Cross-Domain Classification of Sentiment Reviews,
PReMI17(380-386).
Springer DOI
1711
BibRef
Wickramaarachchi, W.U.,
Kariapper, R.K.A.R.,
An approach to get overall emotion from comment text towards a
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ICIVC17(788-792)
IEEE DOI
1708
Automobiles, Electric shock, emotion identification,
latent semantic analysis, natural language processing,
social network, text, processing
BibRef
Pitas, I.,
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The eNTERFACE-05 Audio-Visual Emotion Database,
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IEEE DOI
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Automatic personality prediction from audiovisual data using random
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ICPR16(37-42)
IEEE DOI
1705
Correlation, Feature extraction, Social network services, Speech,
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ICPR16(2866-2871)
IEEE DOI
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Context, Emotion recognition, Feature extraction,
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Cirakman, O.,
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ICPR16(307-312)
IEEE DOI
1705
Attenuation, Computational modeling, Feature extraction,
Psychoacoustic models, Solid modeling, Speech, Training,
affective computing, emotion recognition, particle, filter
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1701
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We are Humor Beings: Understanding and Predicting Visual Humor,
CVPR16(4603-4612)
IEEE DOI
1612
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Impett, L.[Leonardo],
Süsstrunk, S.[Sabine],
Pose and Pathosformel in Aby Warburg's Bilderatlas,
CVAA16(I: 888-902).
Springer DOI
1611
the repeatable formula for the expression of emotion, through the
depiction of human pose in art.
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Abadi, M.K.,
Correa, J.A.M.,
Wache, J.,
Yang, H.[Heng],
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Inference of personality traits and affect schedule by analysis of
spontaneous reactions to affective videos,
FG15(1-8)
IEEE DOI
1508
electrocardiography
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Prasomphan, S.,
Improvement of speech emotion recognition with neural network
classifier by using speech spectrogram,
WSSIP15(73-76)
IEEE DOI
1603
emotion recognition
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Shashidhar, K.G.,
Shivakranthi, B.,
Rao, K.S.,
Ramteke, P.B.,
Contribution of Telugu vowels in identifying emotions,
ICAPR15(1-6)
IEEE DOI
1511
Gaussian processes
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Fernández, X.[Ximena],
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Classification of Basic Human Emotions from Electroencephalography Data,
CIARP15(108-115).
Springer DOI
1511
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Peng, K.C.[Kuan-Chuan],
Chen, T.H.[Tsu-Han],
Sadovnik, A.[Amir],
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A mixed bag of emotions:
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CVPR15(860-868)
IEEE DOI
1510
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Wang, W.[Weiyi],
Athanasopoulos, G.[Georgios],
Patsis, G.[Georgios],
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Real-Time Emotion Recognition from Natural Bodily Expressions in
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ACVR14(424-435).
Springer DOI
1504
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Liu, M.M.[Meng-Meng],
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Emotional Tone-Based Audio Continuous Emotion Recognition,
MMMod15(II: 470-480).
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1501
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Deng, J.[Jun],
Zhang, Z.[Zixing],
Schuller, B.[Bjorn],
Linked Source and Target Domain Subspace Feature Transfer Learning --
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ICPR14(761-766)
IEEE DOI
1412
Artificial neural networks
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Yuncu, E.[Enes],
Hacihabiboglu, H.[Huseyin],
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Automatic Speech Emotion Recognition Using Auditory Models with
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ICPR14(773-778)
IEEE DOI
1412
Databases
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HBU14(30-41).
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1411
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HBU14(42-51).
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1411
Dataset, Human Affect.
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CVPR14(216-223)
IEEE DOI
1409
Communicative Intents
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Kaveeta, V.,
Patanukhom, K.,
Emotional Speech Recognition Using Acoustic Models of Decomposed
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ACPR13(115-119)
IEEE DOI
1408
acoustic signal processing
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Albornoz, E.M.[E. Marcelo],
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Spoken Emotion Recognition Using Deep Learning,
CIARP14(104-111).
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1411
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Earlier: A2, A1, A3, A4, A5:
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Modeling and Visualization of Drama Heritage,
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FG13(1-6)
IEEE DOI
1309
emotion recognition
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FG13(1-6)
IEEE DOI
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magnetoencephalography
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FG13(1-7)
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emotion recognition
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Chapter on Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics continues in
Facial Expressions, Overviews, Surveys, Data .