22.3.6.2.9 Emotion Recognition, from Other Than Faces

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., 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

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

Zhang, S.Q.[Shi-Qing], Zhao, X.M.[Xiao-Ming], Tian, Q.[Qi],
Spontaneous Speech Emotion Recognition Using Multiscale Deep Convolutional LSTM,
AffCom(13), No. 2, April 2022, pp. 680-688.
IEEE DOI 2206
Image segmentation, Spectrogram, Feature extraction, Emotion recognition, Speech recognition, Neural networks, multiscale 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

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

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

Song, P., Zheng, W.,
Feature Selection Based Transfer Subspace Learning for Speech Emotion Recognition,
AffCom(11), No. 3, July 2020, pp. 373-382.
IEEE DOI 2008
Speech recognition, Feature extraction, Speech, Emotion recognition, Robustness, Training, Testing, speech emotion recognition 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

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

Luo, Y.[Yu], Ye, J.B.[Jian-Bo], Adams, Jr., R.B.[Reginald B.], Li, J.[Jia], Newman, M.G.[Michelle G.], Wang, J.Z.[James Z.],
ARBEE: Towards Automated Recognition of Bodily Expression of Emotion in the Wild,
IJCV(128), No. 1, January 2020, pp. 1-25.
Springer DOI 2002
BibRef

Gosztolya, G., Grósz, T., Tóth, L.,
Social Signal Detection by Probabilistic Sampling DNN Training,
AffCom(11), No. 1, January 2020, pp. 164-177.
IEEE DOI 2003
Training, Probabilistic logic, Hidden Markov models, Task analysis, Training data, Neural networks, Speech recognition, laughter detection BibRef

Guo, L.[Lili], Wang, L.B.[Long-Biao], Dang, J.W.[Jian-Wu], Liu, Z.L.[Zhi-Lei], Guan, H.T.[Hao-Tian],
Speaker-aware Speech Emotion Recognition by Fusing Amplitude and Phase Information,
MMMod20(I:14-25).
Springer DOI 2003
BibRef

Li, C., Wang, J., Wang, H., Zhao, M., Li, W., Deng, X.,
Visual-Texual Emotion Analysis With Deep Coupled Video and Danmu Neural Networks,
MultMed(22), No. 6, June 2020, pp. 1634-1646.
IEEE DOI 2005
Danmu, deep multimodal learning, emotion analysis BibRef

Wolfe, H., Peljhan, M., Visell, Y.,
Singing Robots: How Embodiment Affects Emotional Responses to Non-Linguistic Utterances,
AffCom(11), No. 2, April 2020, pp. 284-295.
IEEE DOI 2006
Speech, Robot sensing systems, Psychology, Computers, Visualization, Music, Human robot interaction, non-linguistic utterances, iterative prototyping design BibRef

Tarvainen, J., Laaksonen, J., Takala, T.,
Film Mood and Its Quantitative Determinants in Different Types of Scenes,
AffCom(11), No. 2, April 2020, pp. 313-326.
IEEE DOI 2006
Mood, Estimation, Speech, Visualization, Feature extraction, Cameras, Film, affect, mood, style, content-based analysis BibRef

Nagata, T., Mori, H.,
Defining Laughter Context for Laughter Synthesis with Spontaneous Speech Corpus,
AffCom(11), No. 3, July 2020, pp. 553-559.
IEEE DOI 2008
Speech, Hidden Markov models, Databases, Speech synthesis, Acoustics, Context modeling, Man-machine systems, Laughter, HMM-based speech synthesis BibRef

Colneric, N., Demšar, J.,
Emotion Recognition on Twitter: Comparative Study and Training a Unison Model,
AffCom(11), No. 3, July 2020, pp. 433-446.
IEEE DOI 2008
Twitter, Tagging, Mood, Machine learning, Training, Emotion recognition, Convolutional neural networks, convolutional neural networks BibRef

Ma, Y.[Yue], Ling, C.[Changlong], Wu, J.[Jing],
Exploring the Spatial Distribution Characteristics of Emotions of Weibo Users in Wuhan Waterfront Based on Gender Differences Using Social Media Texts,
IJGI(9), No. 8, 2020, pp. xx-yy.
DOI Link 2008
BibRef

Requardt, A.F.[Alicia F.], Ihme, K.[Klas], Wilbrink, M.[Marc], Wendemuth, A.[Andreas],
Towards affect-aware vehicles for increasing safety and comfort: recognising driver emotions from audio recordings in a realistic driving study,
IET-ITS(14), No. 10, October 2020, pp. 1265-1277.
DOI Link 2009
BibRef

Hajarolasvadi, N.[Noushin], Demirel, H.[Hasan],
Deep facial emotion recognition in video using eigenframes,
IET-IPR(14), No. 14, December 2020, pp. 3536-3546.
DOI Link 2012
BibRef

Huang, Z., Epps, J.,
An Investigation of Partition-Based and Phonetically-Aware Acoustic Features for Continuous Emotion Prediction from Speech,
AffCom(11), No. 4, October 2020, pp. 653-668.
IEEE DOI 2011
Phonetics, Speech, Acoustics, Emotion recognition, Speech recognition, Speech processing, Feature extraction, phonetic feature BibRef

Zhu, Z.J.[Zi-Jiang], Dai, W.H.[Wei-Huang], Hu, Y.[Yi], Li, J.S.[Jun-Shan],
Speech emotion recognition model based on Bi-GRU and Focal Loss,
PRL(140), 2020, pp. 358-365.
Elsevier DOI 2012
Bi-GRU, Focal loss, Speech emotion recognition, Deep learning, CRNN BibRef

Pang, J., Rao, Y., Xie, H., Wang, X., Wang, F.L., Wong, T.L., Li, Q.,
Fast Supervised Topic Models for Short Text Emotion Detection,
Cyber(51), No. 2, February 2021, pp. 815-828.
IEEE DOI 2101
Acceleration, Social networking (online), Prediction algorithms, Training, Feature extraction, Parameter estimation, Text analysis, topic model BibRef

Lara-Álvarez, C., Mitre-Hernandez, H., Flores, J.J., Pérez-Espinosa, H.,
Induction of Emotional States in Educational Video Games Through a Fuzzy Control System,
AffCom(12), No. 1, January 2021, pp. 66-77.
IEEE DOI 2103
Games, Emotion recognition, Speech recognition, Integrated circuits, Acoustics, Task analysis, Feature extraction, educational video games BibRef

Avila, A.R., Akhtar, Z., Santos, J.F., O'Shaughnessy, D., Falk, T.H.,
Feature Pooling of Modulation Spectrum Features for Improved Speech Emotion Recognition in the Wild,
AffCom(12), No. 1, January 2021, pp. 177-188.
IEEE DOI 2103
Feature extraction, Emotion recognition, Frequency modulation, Task analysis, Acoustics, Affective computing, in-the-wild BibRef

Ntalampiras, S.[Stavros],
Speech emotion recognition via learning analogies,
PRL(144), 2021, pp. 21-26.
Elsevier DOI 2103
Affective computing, Speech emotion recognition, Few-shot learning, Deep learning, Online learning BibRef

Girlea, C., Girju, R.,
Decoding the Perception of Sincerity in Dialogues,
AffCom(12), No. 1, January 2021, pp. 2-15.
IEEE DOI 2103
Games, Task analysis, Decoding, Internet, Social network services, Media, Feature extraction, Sincerity, perception in dialogues, dating BibRef

Dang, T.[Ting], Sethu, V.[Vidhyasaharan], Ambikairajah, E.[Eliathamby],
Compensation Techniques for Speaker Variability in Continuous Emotion Prediction,
AffCom(12), No. 2, April 2021, pp. 439-452.
IEEE DOI 2106
Predictive models, Analytical models, Feature extraction, Probabilistic logic, Emotion recognition, Phonetics, computational paralinguistics BibRef

Stappen, L.[Lukas], Baird, A.[Alice], Cambria, E.[Erik], Schuller, B.W.[Björn W.],
Sentiment Analysis and Topic Recognition in Video Transcriptions,
IEEE_Int_Sys(36), No. 2, March 2021, pp. 88-95.
IEEE DOI 2106
Measurement, Sentiment analysis, Semantics, Knowledge based systems, Linguistics, Predictive models, Computational modeling BibRef

Ahn, Y.[Youngdo], Lee, S.J.[Sung Joo], Shin, J.W.[Jong Won],
Cross-Corpus Speech Emotion Recognition Based on Few-Shot Learning and Domain Adaptation,
SPLetters(28), 2021, pp. 1190-1194.
IEEE DOI 2106
Training, Speech recognition, Emotion recognition, Neural networks, Measurement, Feature extraction, Databases, Cross-corpus, unsupervised domain adaptation BibRef

Huang, X.D.[Xiang-Dong], Ren, M.J.[Min-Jie], Han, Q.K.[Qian-Kun], Shi, X.Q.[Xiao-Qi], Nie, J.[Jie], Nie, W.Z.[Wei-Zhi], Liu, A.A.[An-An],
Emotion Detection for Conversations Based on Reinforcement Learning Framework,
MultMedMag(28), No. 2, April 2021, pp. 76-85.
IEEE DOI 2107
Feature extraction, Reinforcement learning, Data mining, Acoustics, Logic gates, Context modeling, Uncertainty BibRef

Wu, Y.[Yang], Zhao, Y.Y.[Yan-Yan], Lu, X.[Xin], Qin, B.[Bing], Wu, Y.[Yin], Sheng, J.[Jian], Li, J.L.[Jin-Long],
Modeling Incongruity between Modalities for Multimodal Sarcasm Detection,
MultMedMag(28), No. 2, April 2021, pp. 86-95.
IEEE DOI 2107
Feature extraction, Acoustics, Visualization, Videos, Sentiment analysis, Face recognition, Acoustic measurements BibRef

Phan, D.A.[Duc-Anh], Matsumoto, Y.J.[Yu-Ji], Shindo, H.[Hiroyuki],
Autoencoder for Semisupervised Multiple Emotion Detection of Conversation Transcripts,
AffCom(12), No. 3, July 2021, pp. 682-691.
IEEE DOI 2109
Motion pictures, Correlation, Social network services, Neural networks, Context modeling, Data models, Training data, autoencoder BibRef

Lotfian, R.[Reza], Busso, C.[Carlos],
Over-Sampling Emotional Speech Data Based on Subjective Evaluations Provided by Multiple Individuals,
AffCom(12), No. 4, October 2021, pp. 870-882.
IEEE DOI 2112
Training data, Emotion recognition, Speech recognition, Deep learning, Machine learning, Neural networks, data augmentation for deep neural network BibRef

Sidorova, J.[Julia], Karlsson, S.[Simon], Rosander, O.[Oliver], Berthier, M.L.[Marcelo L.], Moreno-Torres, I.[Ignacio],
Towards Disorder-Independent Automatic Assessment of Emotional Competence in Neurological Patients with a Classical Emotion Recognition System: Application in Foreign Accent Syndrome,
AffCom(12), No. 4, October 2021, pp. 962-973.
IEEE DOI 2112
Emotion recognition, Biomarkers, Speech recognition, Neurological diseases, Pathology, Computational modeling, foreign accent syndrome BibRef

Gideon, J.[John], McInnis, M.G.[Melvin G.], Provost, E.M.[Emily Mower],
Improving Cross-Corpus Speech Emotion Recognition with Adversarial Discriminative Domain Generalization (ADDoG),
AffCom(12), No. 4, October 2021, pp. 1055-1068.
IEEE DOI 2112
Speech recognition, Training, Emotion recognition, Data models, Testing, Speech processing, Generative adversarial networks, domain generalization BibRef

Khorram, S.[Soheil], McInnis, M.G.[Melvin G.], Provost, E.M.[Emily Mower],
Jointly Aligning and Predicting Continuous Emotion Annotations,
AffCom(12), No. 4, October 2021, pp. 1069-1083.
IEEE DOI 2112
Delays, Emotion recognition, Acoustics, Feature extraction, Predictive models, Acoustic measurements, multi-delay sinc network BibRef

Shukla, J.[Jainendra], Barreda-Ángeles, M.[Miguel], Oliver, J.[Joan], Nandi, G.C., Puig, D.[Domènec],
Feature Extraction and Selection for Emotion Recognition from Electrodermal Activity,
AffCom(12), No. 4, October 2021, pp. 857-869.
IEEE DOI 2112
Feature extraction, Mutual information, Emotion recognition, Frequency-domain analysis, Discrete wavelet transforms, feature selection BibRef

Yang, X.C.[Xiao-Cui], Feng, S.[Shi], Wang, D.L.[Da-Ling], Zhang, Y.F.[Yi-Fei],
Image-Text Multimodal Emotion Classification via Multi-View Attentional Network,
MultMed(23), 2021, pp. 4014-4026.
IEEE DOI 2112
Sentiment analysis, Feature extraction, Task analysis, Analytical models, Visualization, Semantics, multimodal emotion analysis BibRef

Zhao, S.C.[Si-Cheng], Jia, G.[Guoli], Yang, J.F.[Ju-Feng], Ding, G.G.[Gui-Guang], Keutzer, K.[Kurt],
Emotion Recognition From Multiple Modalities: Fundamentals and methodologies,
SPMag(38), No. 6, November 2021, pp. 59-73.
IEEE DOI 2112
Annotations, Computational modeling, Emotion recognition, Optimization, Affective computing BibRef

Gómez-Cañón, J.S.[Juan Sebastián], Cano, E.[Estefanía], Eerola, T.[Tuomas], Herrera, P.[Perfecto], Hu, X.[Xiao], Yang, Y.H.[Yi-Hsuan], Gómez, E.[Emilia],
Music Emotion Recognition: Toward new, robust standards in personalized and context-sensitive applications,
SPMag(38), No. 6, November 2021, pp. 106-114.
IEEE DOI 2112
Emotion recognition, Mood, Heuristic algorithms, Computational modeling, Music, Signal processing algorithms, Prediction algorithms BibRef

Cao, L.[Lei], Zhang, H.J.[Hui-Jun], Feng, L.[Ling],
Building and Using Personal Knowledge Graph to Improve Suicidal Ideation Detection on Social Media,
MultMed(24), 2022, pp. 87-102.
IEEE DOI 2202
Blogs, Social networking (online), Psychology, Stress, Statistics, Sociology, Knowledge engineering, Personal knowledge graph, suicidal ideation detection BibRef

Egorow, O.[Olga], Wendemuth, A.[Andreas],
On Emotions as Features for Speech Overlaps Classification,
AffCom(13), No. 1, January 2022, pp. 175-186.
IEEE DOI 2203
Acoustics, Support vector machines, Statistical analysis, Affective computing, Decision trees, Face, Speech, speech overlaps, automatic classification BibRef

Tan, L.[Liang], Yu, K.P.[Ke-Ping], Lin, L.[Long], Cheng, X.F.[Xiao-Fan], Srivastava, G.[Gautam], Lin, J.C.W.[Jerry Chun-Wei], Wei, W.[Wei],
Speech Emotion Recognition Enhanced Traffic Efficiency Solution for Autonomous Vehicles in a 5G-Enabled Space-Air-Ground Integrated Intelligent Transportation System,
ITS(23), No. 3, March 2022, pp. 2830-2842.
IEEE DOI 2203
Speech recognition, Autonomous vehicles, Satellites, Emotion recognition, Next generation networking, ITS BibRef

Xiao, Z.Z.[Zhong-Zhe], Chen, Y.[Ying], Dou, W.[Weibei], Tao, Z.[Zhi], Chen, L.M.[Li-Ming],
MES-P: An Emotional Tonal Speech Dataset in Mandarin with Distal and Proximal Labels,
AffCom(13), No. 1, January 2022, pp. 408-425.
IEEE DOI 2203
Emotion recognition, Speech recognition, Shape, Speech, Observers, Encoding, Emotional speech, Mandarin, dataset, distal labels, emotion intensities BibRef

Araque, O.[Oscar], Gatti, L.[Lorenzo], Staiano, J.[Jacopo], Guerini, M.[Marco],
DepecheMood++: A Bilingual Emotion Lexicon Built Through Simple Yet Powerful Techniques,
AffCom(13), No. 1, January 2022, pp. 496-507.
IEEE DOI 2203
Manuals, Task analysis, Computational modeling, Twitter, Analytical models, Tagging, Mood, Emotion analysis, emotion lexicon, word embeddings BibRef

Braunschweiler, N.[Norbert], Doddipatla, R.[Rama], Keizer, S.[Simon], Stoyanchev, S.[Svetlana],
Factors in Emotion Recognition With Deep Learning Models Using Speech and Text on Multiple Corpora,
SPLetters(29), 2022, pp. 722-726.
IEEE DOI 2204
Emotion recognition, Speech recognition, Data models, Bit error rate, Deep learning, Acoustics, Training, multimodal BibRef

Zhang, Y.[Yue], Weninger, F.[Felix], Schuller, B.[Björn], Picard, R.W.[Rosalind W.],
Holistic Affect Recognition Using PaNDA: Paralinguistic Non-Metric Dimensional Analysis,
AffCom(13), No. 2, April 2022, pp. 769-780.
IEEE DOI 2206
Task analysis, Speech recognition, Emotion recognition, Databases, Predictive models, Cultural differences, Character recognition, multi-task learning BibRef

Wu, M.[Min], Su, W.J.[Wan-Juan], Chen, L.F.[Lue-Feng], Pedrycz, W.[Witold], Hirota, K.[Kaoru],
Two-Stage Fuzzy Fusion Based-Convolution Neural Network for Dynamic Emotion Recognition,
AffCom(13), No. 2, April 2022, pp. 805-817.
IEEE DOI 2206
Feature extraction, Emotion recognition, Speech recognition, Correlation, Neural networks, Data mining, Fuses, canonical correlation analysis BibRef

Latif, S.[Siddique], Rana, R.[Rajib], Khalifa, S.[Sara], Jurdak, R.[Raja], Epps, J.[Julien], Schuller, B.W.[Björn W.],
Multi-Task Semi-Supervised Adversarial Autoencoding for Speech Emotion Recognition,
AffCom(13), No. 2, April 2022, pp. 992-1004.
IEEE DOI 2206
Task analysis, Emotion recognition, Speech recognition, Hidden Markov models, Semisupervised learning, Training, Australia, representation learning BibRef

Sahu, S.[Saurabh], Gupta, R.[Rahul], Espy-Wilson, C.[Carol],
Modeling Feature Representations for Affective Speech Using Generative Adversarial Networks,
AffCom(13), No. 2, April 2022, pp. 1098-1110.
IEEE DOI 2206
Speech recognition, Emotion recognition, Generative adversarial networks, Data models, low-resource classification BibRef

Xu, X.Z.[Xin-Zhou], Deng, J.[Jun], Cummins, N.[Nicholas], Zhang, Z.X.[Zi-Xing], Zhao, L.[Li], Schuller, B.W.[Björn W.],
Exploring Zero-Shot Emotion Recognition in Speech Using Semantic-Embedding Prototypes,
MultMed(24), 2022, pp. 2752-2765.
IEEE DOI 2206
Prototypes, Emotion recognition, Speech recognition, Annotations, Predictive models, Training, Speech emotion recognition, semantic-embedding prototypes BibRef

Harper, R.[Ross], Southern, J.[Joshua],
A Bayesian Deep Learning Framework for End-To-End Prediction of Emotion From Heartbeat,
AffCom(13), No. 2, April 2022, pp. 985-991.
IEEE DOI 2206
Biomedical monitoring, Bayes methods, Heart beat, Brain modeling, Time series analysis, Computational modeling, Uncertainty, end-to-end learning BibRef

Guo, L.[Lili], Wang, L.[Longbiao], Dang, J.[Jianwu], Fu, Y.H.[Ya-Hui], Liu, J.X.[Jia-Xing], Ding, S.[Shifei],
Emotion Recognition With Multimodal Transformer Fusion Framework Based on Acoustic and Lexical Information,
MultMedMag(29), No. 2, April 2022, pp. 94-103.
IEEE DOI 2208
Acoustics, Feature extraction, Transformers, Emotion recognition, Linguistics, Data mining, Speech recognition BibRef

Dong, G.N.[Guan-Nan], Pun, C.M.[Chi-Man], Zhang, Z.[Zheng],
Temporal Relation Inference Network for Multimodal Speech Emotion Recognition,
CirSysVideo(32), No. 9, September 2022, pp. 6472-6485.
IEEE DOI 2209
Feature extraction, Emotion recognition, Speech recognition, Cognition, Hidden Markov models, Correlation, Task analysis, relation inference network BibRef

Braun, N.[Nadine], Goudbeek, M.[Martijn], Krahmer, E.[Emiel],
Affective Words and the Company They Keep: Studying the Accuracy of Affective Word Lists in Determining Sentence and Word Valence in a Domain-Specific Corpus,
AffCom(13), No. 3, July 2022, pp. 1440-1451.
IEEE DOI 2209
Sentiment analysis, Linguistics, Semantics, Dictionaries, Tools, Analytical models, Companies, Affect analysis, emotional corpora BibRef

Mazzocconi, C.[Chiara], Tian, Y.[Ye], Ginzburg, J.[Jonathan],
What's Your Laughter Doing There? A Taxonomy of the Pragmatic Functions of Laughter,
AffCom(13), No. 3, July 2022, pp. 1302-1321.
IEEE DOI 2209
Taxonomy, Acoustics, Pragmatics, Semantics, Timing, Phonetics, Laughter, taxonomy, dialogue semantics, pragmatics, laughter functions BibRef

Liu, K.[Ke], Wang, D.[Dekui], Wu, D.Y.[Dong-Ya], Liu, Y.[Yutao], Feng, J.[Jun],
Speech Emotion Recognition via Multi-Level Attention Network,
SPLetters(29), 2022, pp. 2278-2282.
IEEE DOI 2212
Feature extraction, Data mining, Mel frequency cepstral coefficient, Time-frequency analysis, speech emotion recognition BibRef

Zhang, H.Q.[Han-Qing], Song, D.W.[Da-Wei],
Towards Contrastive Context-Aware Conversational Emotion Recognition,
AffCom(13), No. 4, October 2022, pp. 1879-1891.
IEEE DOI 2212
Context modeling, Semantics, Emotion recognition, Oral communication, Training, Robustness, contrastive learning BibRef

Kshirsagar, S.R.[Shruti Rajendra], Falk, T.H.[Tiago Henrik],
Quality-Aware Bag of Modulation Spectrum Features for Robust Speech Emotion Recognition,
AffCom(13), No. 4, October 2022, pp. 1892-1905.
IEEE DOI 2212
Modulation, Speech recognition, Emotion recognition, Robustness, Deep learning, Feature extraction, Convolution, context-awareness BibRef

Ren, F.[Fuji], Liu, Z.[Zheng], Kang, X.[Xin],
An Efficient Framework for Constructing Speech Emotion Corpus Based on Integrated Active Learning Strategies,
AffCom(13), No. 4, October 2022, pp. 1929-1940.
IEEE DOI 2212
Labeling, Emotion recognition, Speech recognition, Affective computing, Feature extraction, Costs, Learning systems, imbalanced dataset BibRef

Sridhar, K.[Kusha], Busso, C.[Carlos],
Unsupervised Personalization of an Emotion Recognition System: The Unique Properties of the Externalization of Valence in Speech,
AffCom(13), No. 4, October 2022, pp. 1959-1972.
IEEE DOI 2212
Adaptation models, Speech recognition, Predictive models, Acoustics, Data models, Emotion recognition, Training, valence BibRef

Vazquez-Rodriguez, J.[Juan], Lefebvre, G.[Grégoire], Cumin, J.[Julien], Crowley, J.L.[James L.],
Transformer-Based Self-Supervised Learning for Emotion Recognition,
ICPR22(2605-2612)
IEEE DOI 2212
Emotion recognition, Self-supervised learning, Electrocardiography, Transformers, Physiology BibRef

o Kang, X.[Xin], Shi, X.F.[Xue-Feng], Wu, Y.[Yunong], Ren, F.[Fuji],
Active Learning With Complementary Sampling for Instructing Class-Biased Multi-Label Text Emotion Classification,
AffCom(14), No. 1, January 2023, pp. 523-536.
IEEE DOI 2303
Uncertainty, Predictive models, Annotations, Training data, Support vector machines, Data models, Syntactics, Active learning, text emotion BibRef

Latif, S.[Siddique], Rana, R.[Rajib], Khalifa, S.[Sara], Jurdak, R.[Raja], Qadir, J.[Junaid], Schuller, B.[Björn],
Survey of Deep Representation Learning for Speech Emotion Recognition,
AffCom(14), No. 2, April 2023, pp. 1634-1654.
IEEE DOI 2306
Principal component analysis, Task analysis, Speech recognition, Emotion recognition, Deep learning, Australia, Neurons, unsupervised learning BibRef

Feng, K.[Kexin], Chaspari, T.[Theodora],
Few-Shot Learning in Emotion Recognition of Spontaneous Speech Using a Siamese Neural Network With Adaptive Sample Pair Formation,
AffCom(14), No. 2, April 2023, pp. 1627-1633.
IEEE DOI 2306
Speech recognition, Measurement, Training, Emotion recognition, Transfer learning, Feature extraction, Task analysis, siamese neural network BibRef

Gerczuk, M.[Maurice], Amiriparian, S.[Shahin], Ottl, S.[Sandra], Schuller, B.W.[Björn W.],
EmoNet: A Transfer Learning Framework for Multi-Corpus Speech Emotion Recognition,
AffCom(14), No. 2, April 2023, pp. 1472-1487.
IEEE DOI 2306
Speech recognition, Emotion recognition, Adaptation models, Task analysis, Training, Databases, Feature extraction, multi-corpus BibRef

Harvill, J.[John], Leem, S.G.[Seong-Gyun], AbdelWahab, M.[Mohammed], Lotfian, R.[Reza], Busso, C.[Carlos],
Quantifying Emotional Similarity in Speech,
AffCom(14), No. 2, April 2023, pp. 1376-1390.
IEEE DOI 2306
Task analysis, Emotion recognition, Speech recognition, Affective computing, Face recognition, Measurement, Reliability, speech emotion retrieval BibRef

Aldeneh, Z.[Zakaria], Provost, E.M.[Emily Mower],
You're Not You When You're Angry: Robust Emotion Features Emerge by Recognizing Speakers,
AffCom(14), No. 2, April 2023, pp. 1351-1362.
IEEE DOI 2306
Feature extraction, Emotion recognition, Speech recognition, Acoustics, Task analysis, Neural networks, Speaker recognition, transfer learning BibRef

Lin, W.C.[Wei-Cheng], Busso, C.[Carlos],
Chunk-Level Speech Emotion Recognition: A General Framework of Sequence-to-One Dynamic Temporal Modeling,
AffCom(14), No. 2, April 2023, pp. 1215-1227.
IEEE DOI 2306
Feature extraction, Computational modeling, Task analysis, Speech recognition, Acoustics, Emotion recognition, Databases, chunk-level modeling BibRef

Lian, Z.[Zheng], Liu, B.[Bin], Tao, J.H.[Jian-Hua],
SMIN: Semi-Supervised Multi-Modal Interaction Network for Conversational Emotion Recognition,
AffCom(14), No. 3, July 2023, pp. 2415-2429.
IEEE DOI 2310
BibRef

Liu, Y.[Yaochen], Zhang, Y.Z.[Ya-Zhou], Song, D.W.[Da-Wei],
A Quantum Probability Driven Framework for Joint Multi-Modal Sarcasm, Sentiment and Emotion Analysis,
AffCom(15), No. 1, January 2024, pp. 326-341.
IEEE DOI 2403
Emotion recognition, Task analysis, Sentiment analysis, Correlation, Interference, Context modeling, Analytical models, sentiment analysis BibRef

Zhou, Y.Y.[Yang-Yang], Kang, X.[Xin], Ren, F.[Fuji],
Prompt Consistency for Multi-Label Textual Emotion Detection,
AffCom(15), No. 1, January 2024, pp. 121-129.
IEEE DOI 2403
Emotion recognition, Task analysis, Training, Semantics, Predictive models, Feature extraction, Deep learning, textual emotion detection BibRef

Xu, J.Y.[Jing-Yun], Xie, J.Y.[Jia-Yuan], Cai, Y.[Yi], Lin, Z.H.[Ze-Hang], Leung, H.F.[Ho-Fung], Li, Q.[Qing], Chua, T.S.[Tat-Seng],
Context-Aware Dynamic Word Embeddings for Aspect Term Extraction,
AffCom(15), No. 1, January 2024, pp. 144-156.
IEEE DOI Code:
WWW Link. 2403
Task analysis, Fans, Feature extraction, Data mining, Context modeling, Touch sensitive screens, Portable computers, word embedding BibRef

Prabhu, N.R.[Navin Raj], Lehmann-Willenbrock, N.[Nale], Gerkmann, T.[Timo],
End-to-End Label Uncertainty Modeling in Speech Emotion Recognition Using Bayesian Neural Networks and Label Distribution Learning,
AffCom(15), No. 2, April 2024, pp. 579-592.
IEEE DOI 2406
Uncertainty, Annotations, Standards, Speech recognition, Emotion recognition, Correlation, Bayes methods, t-distributions, uncertainty BibRef

Qi, H.N.[Heng-Nian], Zeng, G.[Gang], Jia, K.[Keke], Zhang, C.[Chu], Wu, X.P.[Xiao-Ping], Li, M.X.[Meng-Xia], Lang, Q.[Qing], Wang, L.X.[Ling-Xuan],
Emotion Recognition Based on Handwriting Using Generative Adversarial Networks and Deep Learning,
IET-Bio(2024), No. 1, 2024, pp. 5351588.
DOI Link 2406
BibRef

Efthymiou, F.[Fotis], Hildebrand, C.[Christian],
Empathy by Design: The Influence of Trembling AI Voices on Prosocial Behavior,
AffCom(15), No. 3, July 2024, pp. 1253-1263.
IEEE DOI 2409
Artificial intelligence, Psychology, Ethics, Social robots, Buildings, Advertising, Visualization, Artificial intelligence, ethics of AI BibRef

Upadhyay, S.G.[Shreya G.], Chien, W.S.[Woan-Shiuan], Su, B.H.[Bo-Hao], Lee, C.C.[Chi-Chun],
Learning With Rater-Expanded Label Space to Improve Speech Emotion Recognition,
AffCom(15), No. 3, July 2024, pp. 1539-1552.
IEEE DOI 2409
Emotion recognition, Multitasking, Task analysis, Affective computing, Training, Speech recognition, Annotations, speech emotion recognition BibRef

Chen, W.D.[Wei-Dong], Xing, X.F.[Xiao-Fen], Chen, P.H.[Pei-Hao], Xu, X.M.[Xiang-Min],
Vesper: A Compact and Effective Pretrained Model for Speech Emotion Recognition,
AffCom(15), No. 3, July 2024, pp. 1711-1724.
IEEE DOI 2409
Training, Emotion recognition, Adaptation models, Cross layer design, Computational modeling, Semantics, representation learning BibRef

Martinez-Lucas, L.[Luz], Lin, W.C.[Wei-Cheng], Busso, C.[Carlos],
Analyzing Continuous-Time and Sentence-Level Annotations for Speech Emotion Recognition,
AffCom(15), No. 3, July 2024, pp. 1754-1768.
IEEE DOI 2409
Annotations, Emotion recognition, Affective computing, Task analysis, Speech recognition, Databases, speech emotion recognition BibRef

Liang, B.[Bin], Gui, L.[Lin], He, Y.L.[Yu-Lan], Cambria, E.[Erik], Xu, R.F.[Rui-Feng],
Fusion and Discrimination: A Multimodal Graph Contrastive Learning Framework for Multimodal Sarcasm Detection,
AffCom(15), No. 4, October 2024, pp. 1874-1888.
IEEE DOI 2412
Visualization, Feature extraction, Optical character recognition, Self-supervised learning, Affective computing, sarcasm detection BibRef

Hallmen, T.[Tobias], Deuser, F.[Fabian], Oswald, N.[Norbert], André, E.[Elisabeth],
Unimodal Multi-Task Fusion for Emotional Mimicry Intensity Prediction,
ABAW24(4657-4665)
IEEE DOI 2410
Speech analysis, Electromagnetic interference, Predictive models, Linguistics, Multitasking, Feature extraction, Emotion, Mimicry, ABAW BibRef

Waligora, P.[Paul], Aslam, M.H.[Muhammad Haseeb], Zeeshan, M.O.[Muhammad Osama], Belharbi, S.[Soufiane], Koerich, A.L.[Alessandro Lameiras], Pedersoli, M.[Marco], Bacon, S.[Simon], Granger, E.[Eric],
Joint Multimodal Transformer for Emotion Recognition in the Wild,
ABAW24(4625-4635)
IEEE DOI Code:
WWW Link. 2410
Emotion recognition, Visualization, Face recognition, Biological system modeling, Video sequences, Speech recognition, Joint Multimodal Transformer BibRef

Porco, A.V.[Andrea Veronica], Kang, D.[Dongshik],
Enhancing Emotion Classification Through Speech and Correlated Emotional Sounds via a Variational Auto-Encoder Model with Prosodic Regularization,
ICCVMI23(1-6)
IEEE DOI 2403
Training, Analytical models, Heuristic algorithms, Speech recognition, Speech enhancement, Data models, empathic systems BibRef

Wen, C.S.[Chang-Song], Jia, G.[Guoli], Yang, J.F.[Ju-Feng],
DIP: Dual Incongruity Perceiving Network for Sarcasm Detection,
CVPR23(2540-2550)
IEEE DOI 2309
BibRef

Chiorrini, A.[Andrea], Diamantini, C.[Claudia], Mircoli, A.[Alex], Potena, D.[Domenico], Storti, E.[Emanuele],
EmotionAlBERTo: Emotion Recognition of Italian Social Media Texts Through BERT,
ICPR22(1706-1711)
IEEE DOI 2212
Emotion recognition, Social networking (online), Text recognition, Bit error rate, Classification algorithms, emotion recognition in italian texts BibRef

Franceschini, R.[Riccardo], Fini, E.[Enrico], Beyan, C.[Cigdem], Conti, A.[Alessandro], Arrigoni, F.[Federica], Ricci, E.[Elisa],
Multimodal Emotion Recognition with Modality-Pairwise Unsupervised Contrastive Loss,
ICPR22(2589-2596)
IEEE DOI 2212
Representation learning, Emotion recognition, Supervised learning, Spatial databases, Labeling BibRef

John, V.[Vijay], Kawanishi, Y.[Yasutomo],
Audio and Video-based Emotion Recognition using Multimodal Transformers,
ICPR22(2582-2588)
IEEE DOI 2212
Deep learning, Emotion recognition, Visualization, Computational modeling, Human-robot interaction, Sensor fusion BibRef

Liu, K.[Ke], Wang, C.[Chen], Chen, J.[Jiayue], Feng, J.[Jun],
Time-Frequency Attention for Speech Emotion Recognition with Squeeze-and-Excitation Blocks,
MMMod22(I:533-543).
Springer DOI 2203
BibRef

Kumar, P.[Puneet], Khokher, V.[Vedanti], Gupta, Y.[Yukti], Raman, B.[Balasubramanian],
Hybrid Fusion Based Approach for Multimodal Emotion Recognition with Insufficient Labeled Data,
ICIP21(314-318)
IEEE DOI 2201
Deep learning, Emotion recognition, Sentiment analysis, Image recognition, Text recognition, Social networking (online), Intermediate and Late Fusion BibRef

Dossou, B.F.P.[Bonaventure F. P.], Gbenou, Y.K.S.[Yeno K. S.],
FSER: Deep Convolutional Neural Networks for Speech Emotion Recognition,
ABAW21(3526-3531)
IEEE DOI 2112
Emotion recognition, Databases, Computer network reliability, Speech recognition, Medical services, Benchmark testing, Reliability BibRef

Risholm, P.[Petter], Ivarsen, P.Ø.[Peter Ørnulf], Haugholt, K.H.[Karl Henrik], Mohammed, A.[Ahmed],
Underwater marker-based pose-estimation with associated uncertainty,
OceanVision21(3706-3714)
IEEE DOI 2112
Uncertainty, Estimation, Object detection, Attenuation BibRef

Deng, D.[Didan], Wu, L.[Liang], Shi, B.E.[Bertram E.],
Iterative Distillation for Better Uncertainty Estimates in Multitask Emotion Recognition,
ABAW21(3550-3559)
IEEE DOI 2112
Measurement, Emotion recognition, Uncertainty, Estimation, Computer architecture BibRef

Lv, F.M.[Feng-Mao], Chen, X.[Xiang], Huang, Y.Y.[Yan-Yong], Duan, L.X.[Li-Xin], Lin, G.S.[Guo-Sheng],
Progressive Modality Reinforcement for Human Multimodal Emotion Recognition from Unaligned Multimodal Sequences,
CVPR21(2554-2562)
IEEE DOI 2111
Emotion recognition, Visualization, Correlation, Natural languages, Benchmark testing, Transformers BibRef

Fu, Y.H.[Ya-Hui], Guo, L.[Lili], Wang, L.B.[Long-Biao], Liu, Z.L.[Zhi-Lei], Liu, J.X.[Jia-Xing], Dang, J.W.[Jian-Wu],
A Sentiment Similarity-oriented Attention Model with Multi-task Learning for Text-based Emotion Recognition,
MMMod21(I:278-289).
Springer DOI 2106
BibRef

Kumar, P.[Puneet], Jain, S.[Sidharth], Raman, B.[Balasubramanian], Roy, P.P.[Partha Pratim], Iwamura, M.[Masakazu],
End-to-end Triplet Loss based Emotion Embedding System for Speech Emotion Recognition,
ICPR21(8766-8773)
IEEE DOI 2105
Emotion recognition, Speech recognition, Computer architecture, Speech processing, Residual neural networks, Affective Computing, Cosine Similarity BibRef

Pyrovolakis, K.[Konstantinos], Tzouveli, P.[Paraskevi], Stamou, G.[George],
Mood detection analyzing lyrics and audio signal based on deep learning architectures,
ICPR21(9363-9370)
IEEE DOI 2105
Deep learning, Training, Mood, Supervised learning, Music, Task analysis, Mood Classification, Transfer Learning BibRef

Wen, X.C.[Xin-Cheng], Liu, K.H.[Kun-Hong], Zhang, W.M.[Wei-Ming], Jiang, K.[Kai],
The Application of Capsule Neural Network Based CNN for Speech Emotion Recognition,
ICPR21(9356-9362)
IEEE DOI 2105
Deep learning, Emotion recognition, Sensitivity, Neural networks, Speech recognition, Feature extraction, Noise measurement, Capsule Network BibRef

Pan, Y.R.[Yue-Ran], Cai, K.J.[Kun-Jing], Cheng, M.[Ming], Zou, X.B.[Xiao-Bing], Li, M.[Ming],
Responsive Social Smile: A Machine Learning based Multimodal Behavior Assessment Framework towards Early Stage Autism Screening,
ICPR21(2240-2247)
IEEE DOI 2105
Autism, Protocols, Databases, Fuses, Machine learning, Speech recognition BibRef

Sharma, A.[Astha], Canavan, S.[Shaun],
Multimodal Physiological-Based Emotion Recognition,
CARE20(101-113).
Springer DOI 2103
BibRef

Scotti, V.[Vincenzo], Galati, F.[Federico], Sbattella, L.[Licia], Tedesco, R.[Roberto],
Combining Deep and Unsupervised Features for Multilingual Speech Emotion Recognition,
CARE20(114-128).
Springer DOI 2103
BibRef

Bakhshi, A.[Ali], Chalup, S.[Stephan],
Multimodal Emotion Recognition Based on Speech and Physiological Signals Using Deep Neural Networks,
MMDLCA20(289-300).
Springer DOI 2103
BibRef

Esposito, A., Amorese, T., Maldonato, N.M., Vinciarelli, A., Torres, M.I., Escalera, S., Cordasco, G.,
Seniors' ability to decode differently aged facial emotional expressions,
FG20(716-722)
IEEE DOI 2102
Face recognition, Emotion recognition, Aging, Decoding, Task analysis, Senior citizens, Portable computers BibRef

Athanasiadis, C., Hortal, E., Asteriadis, S.,
Audio-Based Emotion Recognition Enhancement Through Progressive Gans,
ICIP20(236-240)
IEEE DOI 2011
Domain Adaptation, Affective Computing, Generative Adversarial Networks BibRef

Nguyen, X., Lee, G., Kim, S., Yang, H.,
Audio-Video Based Emotion Recognition Using Minimum Cost Flow Algorithm,
MMVAMTC19(3737-3741)
IEEE DOI 2004
audio signal processing, emotion recognition, feature extraction, graph theory, learning (artificial intelligence), deep learning BibRef

Thao, H.T.P., Herremans, D., Roig, G.,
Multimodal Deep Models for Predicting Affective Responses Evoked by Movies,
CVPM19(1618-1627)
IEEE DOI 2004
audio signal processing, emotion recognition, feature extraction, image sequences, learning (artificial intelligence), neural networks BibRef

Zhou, S.P.[Su-Ping], Jia, J.[Jia], Zhang, L.[Long], Wang, Y.F.[Yan-Feng], Chen, W.[Wei], Meng, F.[Fanbo], Yu, F.[Fei], Shen, J.L.[Jia-Lie],
Inferring Emphasis for Real Voice Data: An Attentive Multimodal Neural Network Approach,
MMMod20(II:52-62).
Springer DOI 2003
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Yu, J., Zheng, W.,
Learning Prediction of Emotional Change on Behaviors,
ICIP19(999-1003)
IEEE DOI 1910
Emotional change prediction, multimodal fusion, deep 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
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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
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Gong, J.T.[Jiang-Tao], Shi, Y.[Yin], Wang, J.[Jue], Shi, D.Q.[Dan-Qing], Xu, Y.Q.[Ying-Qing],
Escape from the Dark Jungle: A 3D Audio Game for Emotion Regulation,
VAMR18(II: 57-76).
Springer DOI 1807
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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
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Sharma, S.[Shikhar], Kumar, P.[Piyush], Kumar, K.[Krishan],
LEXER: LEXicon Based Emotion AnalyzeR,
PReMI17(373-379).
Springer DOI 1711
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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
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Wickramaarachchi, W.U., Kariapper, R.K.A.R.,
An approach to get overall emotion from comment text towards a certain image uploaded to social network using Latent Semantic Analysis,
ICIVC17(788-792)
IEEE DOI 1708
Automobiles, Electric shock, emotion identification, latent semantic analysis, natural language processing, social network, text, processing BibRef

Chakraborty, R., Pandharipande, M., Kopparapu, S.K.,
Spontaneous speech emotion recognition using prior knowledge,
ICPR16(2866-2871)
IEEE DOI 1705
Context, Emotion recognition, Feature extraction, Knowledge based systems, Pragmatics, Speech, Speech recognition, Emotion recognition, call center audio, knowledge-based framework, non-acted emotion, spontaneous, speech BibRef

Cirakman, O., Gunsel, B.,
Online speaker emotion tracking with a dynamic state transition model,
ICPR16(307-312)
IEEE DOI 1705
Attenuation, Computational modeling, Feature extraction, Psychoacoustic models, Solid modeling, Speech, Training, affective computing, emotion recognition, particle, filter BibRef

Moro, A.D.[Angelo D.], Quintero, C.[Christian], Sarmiento, W.J.[Wilson J.],
Narrative Approach to Assess Fear of Heights in Virtual Environments,
ISVC16(I: 691-700).
Springer DOI 1701
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Chandrasekaran, A.[Arjun], Vijayakumar, A.K.[Ashwin K.], Antol, S.[Stanislaw], Bansal, M.[Mohit], Batra, D.[Dhruv], Zitnick, C.L.[C. Lawrence], Parikh, D.[Devi],
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. Crowdsource annotated art. BibRef

Abadi, M.K., Correa, J.A.M., Wache, J., Yang, H.[Heng], Patras, I., Sebe, N.,
Inference of personality traits and affect schedule by analysis of spontaneous reactions to affective videos,
FG15(1-8)
IEEE DOI 1508
electrocardiography BibRef

Prasomphan, S.,
Improvement of speech emotion recognition with neural network classifier by using speech spectrogram,
WSSIP15(73-76)
IEEE DOI 1603
emotion recognition BibRef

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 BibRef

Peng, K.C.[Kuan-Chuan], Chen, T.H.[Tsu-Han], Sadovnik, A.[Amir], Gallagher, A.[Andrew],
A mixed bag of emotions: Model, predict, and transfer emotion distributions,
CVPR15(860-868)
IEEE DOI 1510
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Wang, W.[Weiyi], Athanasopoulos, G.[Georgios], Patsis, G.[Georgios], Enescu, V.[Valentin], Sahli, H.[Hichem],
Real-Time Emotion Recognition from Natural Bodily Expressions in Child-Robot Interaction,
ACVR14(424-435).
Springer DOI 1504
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Liu, M.M.[Meng-Meng], Chen, H.[Hui], Li, Y.[Yang], Zhang, F.J.[Feng-Jun],
Emotional Tone-Based Audio Continuous Emotion Recognition,
MMMod15(II: 470-480).
Springer DOI 1501
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Deng, J.[Jun], Zhang, Z.X.[Zi-Xing], Schuller, B.[Bjorn],
Linked Source and Target Domain Subspace Feature Transfer Learning -- Exemplified by Speech Emotion Recognition,
ICPR14(761-766)
IEEE DOI 1412
Artificial neural networks BibRef

Yuncu, E.[Enes], Hacihabiboglu, H.[Huseyin], Bozsahin, C.[Cem],
Automatic Speech Emotion Recognition Using Auditory Models with Binary Decision Tree and SVM,
ICPR14(773-778)
IEEE DOI 1412
Databases BibRef

Roffo, G.[Giorgio], Giorgetta, C.[Cinzia], Ferrario, R.[Roberta], Cristani, M.[Marco],
Just the Way You Chat: Linking Personality, Style and Recognizability in Chats,
HBU14(30-41).
Springer DOI 1411
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Joo, J.[Jungseock], Li, W.X.[Wei-Xin], Steen, F.F.[Francis F.], Zhu, S.C.[Song-Chun],
Visual Persuasion: Inferring Communicative Intents of Images,
CVPR14(216-223)
IEEE DOI 1409
Communicative Intents BibRef

Kaveeta, V., Patanukhom, K.,
Emotional Speech Recognition Using Acoustic Models of Decomposed Component Words,
ACPR13(115-119)
IEEE DOI 1408
acoustic signal processing BibRef

Albornoz, E.M.[E. Marcelo], Sánchez-Gutiérrez, M.E.[Máximo E.], Martinez-Licona, F.[Fabiola], Rufiner, H.L.[H. Leonardo], Goddard, J.[John],
Spoken Emotion Recognition Using Deep Learning,
CIARP14(104-111).
Springer DOI 1411
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Earlier: A2, A1, A3, A4, A5:
Deep Learning for Emotional Speech Recognition,
MCPR14(311-320).
Springer DOI 1407
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Lombardo, V.[Vincenzo], Pizzo, A.[Antonio],
Modeling and Visualization of Drama Heritage,
MM4CH13(288-297).
Springer DOI 1309
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Liu, X.N.[Xiang-Ning], Ji, Y.[Yunong], Akahane, K., Sato, M.,
Proposal on an image haptization system based on emotional effects of color,
FG13(1-6)
IEEE DOI 1309
emotion recognition BibRef

Abadi, M.K., Kia, M., Subramanian, R., Avesani, P., Sebe, N.,
Decoding affect in videos employing the MEG brain signal,
FG13(1-6)
IEEE DOI 1309
magnetoencephalography BibRef

Liu, P.[Ping], Han, S.Z.[Shi-Zhong], Tong, Y.[Yan],
Improving facial expression analysis using histograms of Log-Transformed Nonnegative Sparse Representation with a Spatial Pyramid Structure,
FG13(1-7)
IEEE DOI 1309
emotion recognition BibRef

Zheng, W.M.[Wen-Ming], Zhou, X.Y.[Xiao-Yan],
Speech emotion recognition based on kernel reduced-rank regression,
ICPR12(1972-1976).
WWW Link. 1302
BibRef

Shibata, T.[Tatsuya], Kijima, Y.[Yohei],
Emotion recognition modeling of sitting postures by using pressure sensors and accelerometers,
ICPR12(1124-1127).
WWW Link. 1302
BibRef

Rahman, A.K.M.M.[A.K.M. Mahbubur], Tanveer, M.I.[M. Iftekhar], Anam, A.I.[Asm Iftekhar], Yeasin, M.[Mohammed],
IMAPS: A smart phone based real-time framework for prediction of affect in natural dyadic conversation,
VCIP12(1-6).
IEEE DOI 1302
BibRef

Benuš, Š.[Štefan], Rusko, M.[Milan],
Prosodic Characteristics and Emotional Meanings of Slovak Hot-Spot Words,
COST08(18-27).
Springer DOI 0810
BibRef

Sita, K.K.[Kumari K.], Suhasini, S., Mohd., Z.P.S.[Zaheer Parvez Shaik],
Statistical estimation of emotions in speech notes by featured term analogy,
ICIIP11(1-6).
IEEE DOI 1112
BibRef

Wang, J.[Jian], Han, Z.Y.[Zhi-Yan], Lun, S.X.[Shu-Xian],
Speech emotion recognition system based on genetic algorithm and neural network,
IASP11(578-582).
IEEE DOI 1112
BibRef

Snel, J.[John], Cullen, C.[Charlie],
Obtaining speech assets for judgement analysis on low-pass filtered emotional speech,
FG11(835-840).
IEEE DOI 1103
BibRef

Tarasov, A.[Alexey], Delany, S.J.[Sarah Jane],
Benchmarking classification models for emotion recognition in natural speech: A multi-corporal study,
FG11(841-846).
IEEE DOI 1103
BibRef

Ouyang, C.Y.[Chao-Ying], Wuying,
The emotional expression of punctuation in the network language,
IASP11(670-672).
IEEE DOI 1112
BibRef

Rabie, A.[Ahmad], Handmann, U.[Uwe],
Fusion of Audio- and Visual Cues for Real-Life Emotional Human Robot Interaction,
DAGM11(346-355).
Springer DOI 1109
BibRef

Inderbitzin, M.[Martin], Valjamae, A.[Aleksander], Calvo, J.M.B.[Jose Maria Blanco], Verschure, P.F.M.J.[Paul F. M. J.], Bernardet, U.[Ulysses],
Expression of emotional states during locomotion based on canonical parameters,
FG11(809-814).
IEEE DOI 1103
BibRef

Petersen, M.K.[Michael Kai], Hansen, L.K.[Lars Kai],
Emotional nodes among lines of lyrics,
FG11(821-826).
IEEE DOI 1103
BibRef

Sezgin, M.C.[Mehmet Cenk], Gunsel, B.[Bilge], Kurt, G.K.[Gunes Karabulut],
A novel perceptual feature set for audio emotion recognition,
FG11(780-785).
IEEE DOI 1103
BibRef

Espinosa, H.P.[Humberto Perez], Garcia, C.A.R.[Carlos A. Reyes], Pineda, L.V.[Luis Villasenor],
Bilingual acoustic feature selection for emotion estimation using a 3D continuous model,
FG11(786-791).
IEEE DOI 1103
BibRef

Kaernbach, C.[Christian],
On dimensions in emotion psychology,
FG11(792-796).
IEEE DOI 1103
BibRef

Guven, E.[Erhan], Bock, P.[Peter],
Speech Emotion Recognition using a backward context,
AIPR10(1-5).
IEEE DOI 1010
BibRef

Tawari, A.[Ashish], Trivedi, M.M.[Mohan M.],
Speech Emotion Analysis in Noisy Real-World Environment,
ICPR10(4605-4608).
IEEE DOI 1008
BibRef

Huang, T.[Ting], Yang, Y.C.[Ying-Chun],
Learning Virtual HD Model for Bi-model Emotional Speaker Recognition,
ICPR10(1614-1617).
IEEE DOI 1008
BibRef

Mahdhaoui, A.[Ammar], Chetouani, M.[Mohamed],
Emotional Speech Classification Based on Multi View Characterization,
ICPR10(4488-4491).
IEEE DOI 1008
BibRef

Bozkurt, E.[Elif], Erzin, E.[Engin], Erdem, C.E.[Cigdem Eroglu], Erdem, A.T.[A. Tanju],
Use of Line Spectral Frequencies for Emotion Recognition from Speech,
ICPR10(3708-3711).
IEEE DOI 1008
BibRef

Kandali, A.B.[Aditya Bihar], Routray, A.[Aurobinda], Basu, T.K.[Tapan Kumar],
Cross-Lingual Vocal Emotion Recognition in Five Native Languages of Assam Using Eigenvalue Decomposition,
PReMI09(519-524).
Springer DOI 0912
BibRef

Koolagudi, S.G.[Shashidhar G.], Rao, K.S.[K. Sreenivasa],
Exploring Speech Features for Classifying Emotions along Valence Dimension,
PReMI09(537-542).
Springer DOI 0912
BibRef

Bhowmick, P.K.[Plaban K.], Basu, A.[Anupam], Mitra, P.[Pabitra], Prasad, A.[Abhishek],
Multi-label Text Classification Approach for Sentence Level News Emotion Analysis,
PReMI09(261-266).
Springer DOI 0912
BibRef

Li, D.D.[Dong-Dong], Yang, Y.C.[Ying-Chun],
Emotional Speech Clustering Based Robust Speaker Recognition System,
CISP09(1-5).
IEEE DOI 0910
BibRef

Shan, Z.Y.[Zhen-Yu], Yang, Y.C.[Ying-Chun],
Scores Selection for Emotional Speaker Recognition,
ICB09(494-502).
Springer DOI 0906
BibRef

Vincent, J.[Jane],
Affiliations, Emotion and the Mobile Phone,
COST08(28-41).
Springer DOI 0810
BibRef

Staroniewicz, P.[Piotr], Majewski, W.[Wojciech],
Polish Emotional Speech Database: Recording and Preliminary Validation,
COST08(42-49).
Springer DOI 0810
BibRef

Bortoluzzi, M.[Maria],
Towards a Framework of Critical Multimodal Analysis: Emotion in a Film Trailer,
COST08(50-62).
Springer DOI 0810
BibRef

Murphy, P.J.[Peter J.], Laukkanen, A.M.[Anne-Maria],
Investigation of Normalised Time of Increasing Vocal Fold Contact as a Discriminator of Emotional Voice Type,
COST08(90-97).
Springer DOI 0810
BibRef

Pribil, J.[Jirí], Pribilová, A.[Anna],
Spectral Flatness Analysis for Emotional Speech Synthesis and Transformation,
COST08(106-115).
Springer DOI 0810
BibRef

Hristova, E.[Evgenia], Grinberg, M.[Maurice], Lalev, E.[Emilian],
Biosignal Based Emotion Analysis of Human-Agent Interactions,
COST08(63-75).
Springer DOI 0810
BibRef

Papa, F.[Filomena], Sapio, B.[Bartolomeo],
Emotional Aspects in User Experience with Interactive Digital Television: A Case Study on Dyslexia Rehabilitation,
COST08(76-89).
Springer DOI 0810
BibRef

Vondra, M.[Martin], Vích, R.[Robert],
Evaluation of Speech Emotion Classification Based on GMM and Data Fusion,
COST08(98-105).
Springer DOI 0810
BibRef

Ser, W.[Wee], Cen, L.[Ling], Yu, Z.L.[Zhu Liang],
A Hybrid PNN-GMM classification scheme for speech emotion recognition,
ICPR08(1-4).
IEEE DOI 0812
BibRef

Shan, Z.Y.[Zhen-Yu], Yang, Y.C.[Ying-Chun],
Learning polynomial function based neutral-emotion GMM transformation for emotional speaker recognition,
ICPR08(1-4).
IEEE DOI 0812
BibRef

Pao, T.L.[Tsang-Long], Chen, Y.T.[Yu-Te], Yeh, J.H.[Jun-Heng], Li, P.J.[Pei-Jia],
Mandarin Emotional Speech Recognition Based on SVM and NN,
ICPR06(I: 1096-1100).
IEEE DOI 0609
BibRef

You, M.Y.[Ming-Yu], Chen, C.[Chun], Bu, J.J.[Jia-Jun], Liu, J.[Jia], Tao, J.H.[Jian-Hua],
Emotional Speech Analysis on Nonlinear Manifold,
ICPR06(III: 91-94).
IEEE DOI 0609
BibRef

van den Broek, E.L.[Egon L.], Schut, M.H.[Marleen H.], Westerink, J.H.D.M.[Joyce H.D.M.], van Herk, J.[Jan], Tuinenbreijer, K.[Kees],
Computing Emotion Awareness Through Facial Electromyography,
CVHCI06(52-63).
Springer DOI 0605
BibRef

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Last update:Mar 17, 2025 at 20:02:03