22.3.6.2.10 Conversational Emotion, Dialog Emotion

Chapter Contents (Back)
Emotion Recognition. Conversational Emotion. Speech Emotion.
See also Audio-Visual Emotion, Audiovisual Emotion Recognition.
See also Emotion Recognition, from Other Than Faces, Speech Emotion.

McKeown, G., Valstar, M.F., Cowie, R., Pantic, M., Schroder, M.,
The SEMAINE Database: Annotated Multimodal Records of Emotionally Colored Conversations between a Person and a Limited Agent,
AffCom(3), No. 1, 2012, pp. 5-17.
IEEE DOI 1202
BibRef

Benyon, D., Gamback, B., Hansen, P., Mival, O., Webb, N.,
How Was Your Day? Evaluating a Conversational Companion,
AffCom(4), No. 3, July 2013, pp. 299-311.
IEEE DOI 1404
human computer interaction BibRef

Stolar, M.N., Lech, M., Sheeber, L.B., Burnett, I.S., Allen, N.B.,
Introducing Emotions to the Modeling of Intra- and Inter-Personal Influences in Parent-Adolescent Conversations,
AffCom(4), No. 4, October 2013, pp. 372-385.
IEEE DOI 1406
behavioural sciences computing 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

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

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

Hu, J.X.[Jia-Xiong], Huang, Y.[Yun], Hu, X.Z.[Xiao-Zhu], Xu, Y.Q.[Ying-Qing],
The Acoustically Emotion-Aware Conversational Agent With Speech Emotion Recognition and Empathetic Responses,
AffCom(14), No. 1, January 2023, pp. 17-30.
IEEE DOI 2303
Emotion recognition, Speech recognition, Databases, Sentiment analysis, Games, Convolutional neural networks, intelligent agents 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

Hou, M.X.[Mi-Xiao], Zhang, Z.[Zheng], Liu, C.[Chang], Lu, G.M.[Guang-Ming],
Semantic Alignment Network for Multi-Modal Emotion Recognition,
CirSysVideo(33), No. 9, September 2023, pp. 5318-5329.
IEEE DOI Code:
WWW Link. 2310
BibRef

Dai, Y.J.[Yi-Jing], Li, Y.J.[Ying-Jian], Chen, D.P.[Dong-Peng], Li, J.X.[Jin-Xing], Lu, G.M.[Guang-Ming],
Multimodal Decoupled Distillation Graph Neural Network for Emotion Recognition in Conversation,
CirSysVideo(34), No. 10, October 2024, pp. 9910-9924.
IEEE DOI Code:
WWW Link. 2411
Emotion recognition, Graph neural networks, Context modeling, Message passing, Visualization, multimodal fusion BibRef

Li, J.[Jiang], Wang, X.P.[Xiao-Ping], Lv, G.Q.[Guo-Qing], Zeng, Z.G.[Zhi-Gang],
GraphCFC: A Directed Graph Based Cross-Modal Feature Complementation Approach for Multimodal Conversational Emotion Recognition,
MultMed(26), 2024, pp. 77-89.
IEEE DOI 2401
BibRef

Yang, K.[Kailai], Zhang, T.[Tianlin], Ananiadou, S.[Sophia],
Disentangled Variational Autoencoder for Emotion Recognition in Conversations,
AffCom(15), No. 2, April 2024, pp. 508-518.
IEEE DOI 2406
Task analysis, Emotion recognition, Hidden Markov models, Context modeling, Decoding, Oral communication, disentangled representations BibRef

Lu, N.N.[Nan-Nan], Han, Z.Y.[Zhi-Yuan], Tan, Z.[Zhen],
A Hypergraph Based Contextual Relationship Modeling Method for Multimodal Emotion Recognition in Conversation,
MultMed(27), 2025, pp. 2243-2255.
IEEE DOI 2505
Emotion recognition, Context modeling, Oral communication, Data models, Long short term memory, Feature extraction, Semantics, hypergraph convolution BibRef

Chien, W.S.[Woan-Shiuan], Upadhyay, S.G.[Shreya G.], Lin, W.C.[Wei-Cheng], Busso, C.[Carlos], Lee, C.C.[Chi-Chun],
Differential Impacts of Monologue and Conversation on Speech Emotion Recognition,
AffCom(16), No. 2, April 2025, pp. 485-498.
IEEE DOI 2506
Emotion recognition, Acoustics, Databases, Oral communication, Training, Speech recognition, Affective computing, Data collection, acoustic variability BibRef

Shou, Y.T.[Yun-Tao], Liu, H.[Huan], Cao, X.[Xiangyong], Meng, D.Y.[De-Yu], Dong, B.[Bo],
A Low-Rank Matching Attention Based Cross-Modal Feature Fusion Method for Conversational Emotion Recognition,
AffCom(16), No. 2, April 2025, pp. 1177-1189.
IEEE DOI 2506
Feature extraction, Emotion recognition, Transformers, Vectors, Semantics, Tensors, Fuses, Computational complexity, Overfitting, multimodal emotion recognition BibRef

Oh, H.S.[Hyung-Seok], Lee, S.H.[Sang-Hoon], Cho, D.H.[Deok-Hyeon], Lee, S.W.[Seong-Whan],
DurFlex-EVC: Duration-Flexible Emotional Voice Conversion Leveraging Discrete Representations Without Text Alignment,
AffCom(16), No. 3, July 2025, pp. 1660-1674.
IEEE DOI 2509
Feature extraction, Autoencoders, Context modeling, Transformers, Acoustics, Speech recognition, Computational modeling, Vocoders, style disentanglement BibRef

Chu, Y.Q.[Yu-Qi], Liao, L.[Lizi], Zhou, Z.Y.[Zhi-Yuan], Ngo, C.W.[Chong-Wah], Hong, R.C.[Ri-Chang],
Towards Multimodal Emotional Support Conversation Systems,
MultMed(27), 2025, pp. 8276-8287.
IEEE DOI 2511
Emotion recognition, Mental health, Artificial intelligence, Videos, Employee welfare, Conversational artificial intelligence, multimodality BibRef

Cao, Y.[YuKun], Huang, L.[Luobin], Tang, Y.J.[Yi-Jia],
PeTracker: Poincaré-Based Dual-Strategy Emotion Tracker for Emotion Recognition in Conversation,
AffCom(16), No. 3, July 2025, pp. 2020-2032.
IEEE DOI 2509
Emotion recognition, Contrastive learning, Semantics, Context modeling, Oral communication, Feature extraction, Training, emotion recognition in conversation BibRef

Shen, S.Y.[Si-Yuan], Liu, F.[Feng], Wang, H.Y.[Han-Yang], Zhou, A.[Aimin],
Towards Speaker-Unknown Emotion Recognition in Conversation via Progressive Contrastive Deep Supervision,
AffCom(16), No. 3, July 2025, pp. 2261-2273.
IEEE DOI 2509
Emotion recognition, Training, Feature extraction, Oral communication, Speaker recognition, Affective computing, deep supervision BibRef

Yang, Z.Y.[Zhen-Yu], Zhang, Z.B.[Zhi-Bo], Cheng, Y.[Yuhu], Zhang, T.[Tong], Wang, X.S.[Xue-Song],
Semantic and Emotional Dual Channel for Emotion Recognition in Conversation,
AffCom(16), No. 3, July 2025, pp. 1885-1902.
IEEE DOI 2509
Emotion recognition, Semantics, Context modeling, Accuracy, Knowledge engineering, Data mining, Analytical models, dialogue emotion propagation graph BibRef

Tu, G.[Geng], Jing, R.[Ran], Liang, B.[Bin], Yu, Y.[Yue], Yang, M.[Min], Qin, B.[Bing], Xu, R.F.[Rui-Feng],
Generalizing to Unseen Speakers: Multimodal Emotion Recognition in Conversations With Speaker Generalization,
AffCom(16), No. 4, October 2025, pp. 3043-3054.
IEEE DOI 2512
Uncertainty, Prototypes, Emotion recognition, Context modeling, Visualization, Training, Oral communication, Graph neural networks, contrastive learning BibRef

Rao, Y.J.[Yu-Jing], Cao, M.[Min], Ye, M.[Mang],
Contextual Graph Reconstruction and Emotional Variation Learning for Conversational Emotion Recognition,
AffCom(16), No. 4, October 2025, pp. 3067-3080.
IEEE DOI 2512
Emotion recognition, Image reconstruction, Context modeling, Oral communication, Affective computing, Data mining, emotional variation BibRef

Lai, Q.F.[Qi-Feng], Liu, H.[Han], Li, Y.M.[Yuan-Man], Gong, Z.G.[Zhi-Guo], Wang, W.[Wei],
Emotions Like Human: Self-Supervised Emotion Label Augmentation for Emotion Recognition in Conversation,
AffCom(17), No. 1, January 2026, pp. 817-828.
IEEE DOI 2603
Emotion recognition, Context modeling, Training, Computational modeling, Fuses, Data models, natural language processing BibRef

An, X.C.[Xiao-Chun], Zhang, X.[Xu], Li, X.[Xiaoge], Pei, E.[Ercheng], Yan, Q.L.[Qing-Li], He, L.[Lang],
LLM-driven fine-grained emotion parsing and parameterized mapping for conversational TTS,
PR(179), 2026, pp. 113544.
Elsevier DOI 2606
Conversational TTS, Large language models(LLMs), Fine-grained emotion parsing, Parameterized mapping, Prompt enhancement BibRef

Suh, J.[Jina], Le, L.[Lindy], Shayegani, E.[Erfan], Ramos, G.[Gonzalo], Amores, J.[Judith], Ong, D.C.[Desmond C.], Czerwinski, M.[Mary], Hernandez, J.[Javier],
SENSE-7: Taxonomy and Dataset for Measuring User Perceptions of Empathy in Sustained Human-AI Conversations,
AffCom(17), No. 2, April 2026, pp. 2227-2244.
IEEE DOI 2606
Artificial intelligence, Oral communication, Taxonomy, Psychology, Annotations, Accuracy, Large language models, Affective computing, dataset BibRef

Guo, L.[Lili], Cui, Y.[Yanan], Song, Y.K.[Yi-Kang], Hou, H.W.[Hai-Wei], Ding, S.F.[Shi-Fei],
EmoKEG: Knowledge-enhanced heterogeneous graph for emotion recognition in conversation,
PR(179), 2026, pp. 113500.
Elsevier DOI 2606
Emotion recognition in conversation, COMET Knowledge extraction, Common knowledge BibRef

Zhang, G.Z.[Guang-Zi], Zhang, Y.P.[Yu-Peng], Wang, L.[Liang], Zhang, J.[Junru], Cai, X.Q.[Xing-Quan],
CAS-ODE: Jointly Learning Adaptive Structures and Continuous Dynamics for Emotion Recognition in Conversation,
SPLetters(33), 2026, pp. 2405-2409.
IEEE DOI 2606
Modeling, Learning (artificial intelligence), Emotion recognition, Dynamics, Evolution (biology), Permission, spatiotemporal modeling BibRef

Dong, Q.[Qian], Ren, W.H.[Wei-Hong], Gao, Y.[Yu], Liu, J.Z.[Jian-Zhuang], Liu, H.H.[Hong-Hai],
Context Modeling With Multimodal Prompts for Emotion Recognition in Conversation,
MultMed(28), 2026, pp. 5288-5302.
IEEE DOI 2607
Emotion recognition, Visualization, Feature extraction, Context modeling, Facial expressions, Graph neural networks, multimodal prompt BibRef

Park, S.C.[Sun-Chan], Kim, H.S.[Hyung Soon], Kong, K.[Kyeongbo],
Group-Wise Layer Aggregation of Self-Supervised Representations for Speech Emotion Recognition,
SPLetters(33), 2026, pp. 2705-2709.
IEEE DOI 2607
Modeling, Speech, Emotion recognition, Training, Labeling, Self-supervised learning, Statistics, Signal processing, self-supervised models BibRef

Xu, X.[Xu], Muhammad, G.[Ghulam],
Quantum-driven attention and relation-aware distillation for multi-modal emotion recognition in conversations,
PR(180), 2026, pp. 114157.
Elsevier DOI 2608
Emotion recognition in conversations, Multi-modal information, Attention mechanism, Knowledge distillation BibRef

Zhang, J.[Jian], Zhao, P.Z.[Pei-Zheng], Wang, Q.[Qiufeng], Liu, H.[Han], Lu, D.M.[Dong-Ming], Wu, F.Y.[Fang-Yu],
SENTI: Semantic Enhancement and Relation Propagation Network for multimodal emotion recognition in conversations,
PR(180), 2026, pp. 114019.
Elsevier DOI 2608
Multimodal emotion recognition in conversations, Hypergraph neural networks, Semantic enhancement BibRef


Liu, H.Y.[Hai-Yang], Zhu, Z.H.[Zi-Hao], Iwamoto, N.[Naoya], Peng, Y.C.[Yi-Chen], Li, Z.Q.[Zheng-Qing], Zhou, Y.[You], Bozkurt, E.[Elif], Zheng, B.[Bo],
BEAT: A Large-Scale Semantic and Emotional Multi-modal Dataset for Conversational Gestures Synthesis,
ECCV22(VII:612-630).
Springer DOI 2211
Dataset, Emotions. BibRef

Chudasama, V.[Vishal], Kar, P.[Purbayan], Gudmalwar, A.[Ashish], Shah, N.[Nirmesh], Wasnik, P.[Pankaj], Onoe, N.[Naoyuki],
M2FNet: Multi-modal Fusion Network for Emotion Recognition in Conversation,
MULA22(4651-4660)
IEEE DOI 2210
Human computer interaction, Emotion recognition, Visualization, Adaptation models, Benchmark testing, Feature extraction, Robustness 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

Aubrey, A.J.[Andrew J.], Marshall, D.[David], Rosin, P.L.[Paul L.], Vendeventer, J.[Jason], Cunningham, D.W.[Douglas W.], Wallraven, C.[Christian],
Cardiff Conversation Database (CCDb): A Database of Natural Dyadic Conversations,
LV13(277-282)
IEEE DOI 1309
Dataset, Facial Expressions. Conversations; Database; Facial Expressions BibRef

Marcos-Ramiro, A., Pizarro-Perez, D., Marron-Romera, M., Nguyen, L., Gatica-Perez, D.[Daniel],
Body communicative cue extraction for conversational analysis,
FG13(1-8)
IEEE DOI 1309
feature extraction. Non-verbal communication. Gestures, etc. BibRef

Escalera, S.[Sergio], Puertas, E.[Eloi], Radeva, P.I.[Petia I.], Pujol, O.[Oriol],
Multi-modal laughter recognition in video conversations,
CVPR4HB09(110-115).
IEEE DOI 0906
BibRef

Chapter on Face Recognition, Human Pose, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics continues in
Emotion Recognition, from Other Than Faces, Speech Emotion .


Last update:Aug 19, 2026 at 13:26:35