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Multi-modal conversation emotion recognition (MCER) aims to recognize and track the speaker's emotional state using text, speech, and visual information in the conversation scene.
Naive Bayes for regression
Eibe Frank, Leonard Trigg, Geoffrey Holmes, and Ian H Witten. 2000 · 2000
Earlier work this paper cites.
Speech emotion recognition based on HMM and SVM. In 2005 International Conference on Machine Learning and Cybernetics , Vol. 8. IEEE, 4898–4901
Yi-Lin Lin and Gang Wei. 2005 · 2005
Earlier work this paper cites.
Emotion recognition in speech signal using emotion-extracting binary decision trees
Jarosław Cichosz and Krzysztof Slot. 2007 · 2007
Earlier work this paper cites.
GMM supervector based SVM with spectral features for speech emotion recognition. In 2007 IEEE International Conference on Acoustics, Speech and Signal Processing-ICASSP’07 , Vol. 4. IEEE, IV–413
Hao Hu, Ming-Xing Xu, and Wei Wu. 2007 · 2007
Earlier work this paper cites.
IEMOCAP: Interactive emotional dyadic motion capture database
Carlos Busso, Murtaza Bulut, Chi-Chun Lee, Abe Kazemzadeh, Emily Mower, Samuel Kim, Jeannette N Chang, Sungbok Lee, and Shrikanth S Narayanan. 2008 · 2008
Earlier work this paper cites.
Emotion recognition using a hierarchical binary decision tree approach
Chi-Chun Lee, Emily Mower, Carlos Busso, Sungbok Lee, and Shrikanth Narayanan. 2011 · 2011
Earlier work this paper cites.
The semaine database: Annotated multimodal records of emotionally colored conversations between a person and a limited agent
Gary McKeown, Michel Valstar, Roddy Cowie, Maja Pantic, and Marc Schroder. 2011 · 2011
Earlier work this paper cites.
Towards multimodal sentiment analysis: Harvesting opinions from the web. In Proceedings of the 13th international conference on multimodal interfaces . 169–176
Louis-Philippe Morency, Rada Mihalcea, and Payal Doshi. 2011 · 2011
Earlier work this paper cites.
Whisper: Tracing the spatiotemporal process of information diffusion in real time
Nan Cao, Yu-Ru Lin, Xiaohua Sun, David Lazer, Shixia Liu, and Huamin Qu. 2012 · 2012
Earlier work this paper cites.
Ensemble of svm trees for multimodal emotion recognition. In Proceedings of the 2012 Asia Pacific Signal and Information Processing Association Annual Summit and Conference . IEEE, 1–4
Viktor Rozgić, Sankaranarayanan Ananthakrishnan, Shirin Saleem, Rohit Kumar, and Rohit Prasad. 2012 · 2012
Earlier work this paper cites.
Utterance-level multimodal sentiment analysis. In Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) . 973–982
Verónica Pérez-Rosas, Rada Mihalcea, and Louis-Philippe Morency. 2013 · 2013
Earlier work this paper cites.
Convolutional Neural Networks for Sentence Classification. In Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP) . Association for Computational Linguistics
Yoon Kim. 2014 · 2014
Earlier work this paper cites.
Deep convolutional neural network textual features and multiple kernel learning for utterance-level multimodal sentiment analysis. In Proceedings of the 2015 conference on empirical methods in natural language processing . 2539–2544
Soujanya Poria, Erik Cambria, and Alexander Gelbukh. 2015 · 2015
Earlier work this paper cites.
Learning spatiotemporal features with 3d convolutional networks. In Proceedings of the IEEE international conference on computer vision . 4489–4497
Du Tran, Lubomir Bourdev, Rob Fergus, Lorenzo Torresani, and Manohar Paluri. 2015 · 2015
Earlier work this paper cites.
Dictionary based approach to sentiment analysis-a review
Tanvi Hardeniya and Dilipkumar A Borikar. 2016 · 2016
Earlier work this paper cites.
Multimodal analysis and prediction of persuasiveness in online social multimedia
Sunghyun Park, Han Suk Shim, Moitreya Chatterjee, Kenji Sagae, and Louis-Philippe Morency. 2016 · 2016
Earlier work this paper cites.
Convolutional MKL based multimodal emotion recognition and sentiment analysis. In 2016 IEEE 16th international conference on data mining (ICDM) . IEEE, 439–448
Soujanya Poria, Iti Chaturvedi, Erik Cambria, and Amir Hussain. 2016 · 2016
Earlier work this paper cites.
A combined rule-based & machine learning audio-visual emotion recognition approach
Kah Phooi Seng, Li-Minn Ang, and Chien Shing Ooi. 2016 · 2016
Earlier work this paper cites.
Benchmarking multimodal sentiment analysis. In Computational Linguistics and Intelligent Text Processing: 18th International Conference, CICLing 2017, Budapest, Hungary, April 17–23, 2017, Revised Selected Papers, Part II 18 . Springer, 166–179
Erik Cambria, Devamanyu Hazarika, Soujanya Poria, Amir Hussain, and RBV Subramanyam. 2018 · 2017
Earlier work this paper cites.
DailyDialog: A Manually Labelled Multi-turn Dialogue Dataset. In Proceedings of the Eighth International Joint Conference on Natural Language Processing (Volume 1: Long Papers) . 986–995
Yanran Li, Hui Su, Xiaoyu Shen, Wenjie Li, Ziqiang Cao, and Shuzi Niu. 2017 · 2017
Earlier work this paper cites.
Context-dependent sentiment analysis in user-generated videos. In Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (volume 1: Long papers) . 873–883
Soujanya Poria, Erik Cambria, Devamanyu Hazarika, Navonil Majumder, Amir Zadeh, and Louis-Philippe Morency. 2017 · 2017
Earlier work this paper cites.
Select-additive learning: Improving generalization in multimodal sentiment analysis. In 2017 IEEE International Conference on Multimedia and Expo (ICME) . IEEE, 949–954
Haohan Wang, Aaksha Meghawat, Louis-Philippe Morency, and Eric P Xing. 2017 · 2017
Earlier work this paper cites.
Tensor Fusion Network for Multimodal Sentiment Analysis. In Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing . 1103–1114
Amir Zadeh, Minghai Chen, Soujanya Poria, Erik Cambria, and Louis-Philippe Morency. 2017 · 2017
Earlier work this paper cites.
Emotion detection on tv show transcripts with sequence-based convolutional neural networks
Sayyed M Zahiri and Jinho D Choi. 2017 · 2017
Earlier work this paper cites.
Openface 2.0: Facial behavior analysis toolkit. In 2018 13th IEEE international conference on automatic face & gesture recognition (FG 2018) . IEEE, 59–66
Tadas Baltrusaitis, Amir Zadeh, Yao Chong Lim, and Louis-Philippe Morency. 2018 · 2018
Earlier work this paper cites.
Contextual inter-modal attention for multi-modal sentiment analysis. In proceedings of the 2018 conference on empirical methods in natural language processing . 3454–3466
Deepanway Ghosal, Md Shad Akhtar, Dushyant Chauhan, Soujanya Poria, Asif Ekbal, and Pushpak Bhattacharyya. 2018 · 2018
Earlier work this paper cites.
Icon: Interactive conversational memory network for multimodal emotion detection. In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing . 2594–2604
Devamanyu Hazarika, Soujanya Poria, Rada Mihalcea, Erik Cambria, and Roger Zimmermann. 2018a · 2018
Earlier work this paper cites.
Conversational memory network for emotion recognition in dyadic dialogue videos. In Proceedings of the conference. Association for Computational Linguistics. North American Chapter. Meeting , Vol. 2018. NIH Public Access, 2122
Devamanyu Hazarika, Soujanya Poria, Amir Zadeh, Erik Cambria, Louis-Philippe Morency, and Roger Zimmermann. 2018b · 2018
Earlier work this paper cites.
EmotionLines: An Emotion Corpus of Multi-Party Conversations. In Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018)
Chao-Chun Hsu, Sheng-Yeh Chen, Chuan-Chun Kuo, Ting-Hao Huang, and Lun-Wei Ku. 2018 · 2018
Earlier work this paper cites.
Speech emotion recognition based on feature selection and extreme learning machine decision tree
Zhen-Tao Liu, Min Wu, Wei-Hua Cao, Jun-Wei Mao, Jian-Ping Xu, and Guan-Zheng Tan. 2018b · 2018
Earlier work this paper cites.
Advanced LSTM: A study about better time dependency modeling in emotion recognition. In 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) . IEEE, 2906–2910
Fei Tao and Gang Liu. 2018 · 2018
Earlier work this paper cites.
Integrating Recurrence Dynamics for Speech Emotion Recognition
Efthymios Tzinis, Georgios Paraskevopoulos, Christos Baziotis, and Alexandros Potamianos. 2018 · 2018
Earlier work this paper cites.
Bagged support vector machines for emotion recognition from speech
Anjali Bhavan, Pankaj Chauhan, Rajiv Ratn Shah, et al · 2019
Earlier work this paper cites.
Understanding emotions in text using deep learning and big data
Ankush Chatterjee, Umang Gupta, Manoj Kumar Chinnakotla, Radhakrishnan Srikanth, Michel Galley, and Puneet Agrawal. 2019 · 2019
Earlier work this paper cites.
Audio word2vec: Sequence-to-sequence autoencoding for unsupervised learning of audio segmentation and representation
Yi-Chen Chen, Sung-Feng Huang, Hung-yi Lee, Yu-Hsuan Wang, and Chia-Hao Shen. 2019 · 2019
Earlier work this paper cites.
DialogueGCN: A Graph Convolutional Neural Network for Emotion Recognition in Conversation. In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing . Association for Computational Linguistics
Deepanway Ghosal, Navonil Majumder, Soujanya Poria, Niyati Chhaya, and Alexander Gelbukh. 2019 · 2019
Earlier work this paper cites.
Curriculum learning for speech emotion recognition from crowdsourced labels
Reza Lotfian and Carlos Busso. 2019 · 2019
Earlier work this paper cites.
Emotion recognition using multimodal residual LSTM network. In Proceedings of the 27th ACM international conference on multimedia . 176–183
Jiaxin Ma, Hao Tang, Wei-Long Zheng, and Bao-Liang Lu. 2019 · 2019
Earlier work this paper cites.
Locally confined modality fusion network with a global perspective for multimodal human affective computing
Sijie Mai, Songlong Xing, and Haifeng Hu. 2019b · 2019
Earlier work this paper cites.
Dialoguernn: An attentive rnn for emotion detection in conversations. In Proceedings of the AAAI conference on artificial intelligence , Vol. 33. 6818–6825
Navonil Majumder, Soujanya Poria, Devamanyu Hazarika, Rada Mihalcea, Alexander Gelbukh, and Erik Cambria. 2019 · 2019
Earlier work this paper cites.
Found in translation: Learning robust joint representations by cyclic translations between modalities. In Proceedings of the AAAI Conference on Artificial Intelligence , Vol. 33. 6892–6899
Hai Pham, Paul Pu Liang, Thomas Manzini, Louis-Philippe Morency, and Barnabás Póczos. 2019 · 2019
Earlier work this paper cites.
MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations. In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics . Association for Computational Linguistics
Soujanya Poria, Devamanyu Hazarika, Navonil Majumder, Gautam Naik, Erik Cambria, and Rada Mihalcea. 2019 · 2019
Earlier work this paper cites.
Multimodal transformer for unaligned multimodal language sequences. In Proceedings of the conference. Association for Computational Linguistics. Meeting , Vol. 2019. NIH Public Access, 6558
Yao-Hung Hubert Tsai, Shaojie Bai, Paul Pu Liang, J Zico Kolter, Louis-Philippe Morency, and Ruslan Salakhutdinov. 2019 · 2019
Earlier work this paper cites.
Words can shift: Dynamically adjusting word representations using nonverbal behaviors. In Proceedings of the AAAI Conference on Artificial Intelligence , Vol. 33. 7216–7223
Yansen Wang, Ying Shen, Zhun Liu, Paul Pu Liang, Amir Zadeh, and Louis-Philippe Morency. 2019 · 2019
Earlier work this paper cites.
Speech emotion classification using attention-based LSTM
Yue Xie, Ruiyu Liang, Zhenlin Liang, Chengwei Huang, Cairong Zou, and Björn Schuller. 2019 · 2019
Earlier work this paper cites.
Knowledge-Enriched Transformer for Emotion Detection in Textual Conversations. In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP) . 165–176
Peixiang Zhong, Di Wang, and Chunyan Miao. 2019 · 2019
Earlier work this paper cites.
Cross-network skip-gram embedding for joint network alignment and link prediction
Xingbo Du, Junchi Yan, Rui Zhang, and Hongyuan Zha. 2020 · 2020
Earlier work this paper cites.
COSMIC: COmmonSense knowledge for eMotion Identification in Conversations. In Findings of the Association for Computational Linguistics: EMNLP 2020 . 2470–2481
Deepanway Ghosal, Navonil Majumder, Alexander Gelbukh, Rada Mihalcea, and Soujanya Poria. 2020 · 2020
Earlier work this paper cites.
Misa: Modality-invariant and-specific representations for multimodal sentiment analysis. In Proceedings of the 28th ACM international conference on multimedia . 1122–1131
Devamanyu Hazarika, Roger Zimmermann, and Soujanya Poria. 2020 · 2020
Earlier work this paper cites.
Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel. 2020 · 2020
Earlier work this paper cites.
Multimodal transformer fusion for continuous emotion recognition. In ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) . IEEE, 3507–3511
Jian Huang, Jianhua Tao, Bin Liu, Zheng Lian, and Mingyue Niu. 2020 · 2020
Earlier work this paper cites.
Relation-aware graph attention networks with relational position encodings for emotion recognition in conversations. In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) . 7360–7370
Taichi Ishiwatari, Yuki Yasuda, Taro Miyazaki, and Jun Goto. 2020 · 2020
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Time–frequency representation and convolutional neural network-based emotion recognition
Smith K Khare and Varun Bajaj. 2020 · 2020
Cited alongside, same era.
Exploiting multi-cnn features in cnn-rnn based dimensional emotion recognition on the omg in-the-wild dataset
Dimitrios Kollias and Stefanos Zafeiriou. 2020 · 2020
Cited alongside, same era.
Multi-task semi-supervised adversarial autoencoding for speech emotion recognition
Siddique Latif, Rajib Rana, Sara Khalifa, Raja Jurdak, Julien Epps, and Björn W Schuller. 2020 · 2020
Cited alongside, same era.
Hitrans: A transformer-based context-and speaker-sensitive model for emotion detection in conversations. In Proceedings of the 28th International Conference on Computational Linguistics . 4190–4200
Emotion recognition for everyday life using physiological signals from wearables: A systematic literature review
Stanislaw Saganowski, Bartosz Perz, Adam Polak, and Przemyslaw Kazienko. 2022 · 2022
Later among the works it cites.
Conversational emotion recognition studies based on graph convolutional neural networks and a dependent syntactic analysis
Yuntao Shou, Tao Meng, Wei Ai, Sihan Yang, and Keqin Li. 2022 · 2022
Later among the works it cites.
Context-and sentiment-aware networks for emotion recognition in conversation
Geng Tu, Jintao Wen, Cheng Liu, Dazhi Jiang, and Erik Cambria. 2022 · 2022
Later among the works it cites.
M2R2: Missing-Modality Robust emotion Recognition framework with iterative data augmentation
Ning Wang, Hui Cao, Jun Zhao, Ruilin Chen, Dapeng Yan, and Jie Zhang. 2022 · 2022
Later among the works it cites.
Sentiment Word Aware Multimodal Refinement for Multimodal Sentiment Analysis with ASR Errors. In Findings of the Association for Computational Linguistics: ACL 2022 . 1397–1406
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Cited alongside, same era.
Integrating multimodal information in large pretrained transformers. In Proceedings of the conference. Association for Computational Linguistics. Meeting , Vol. 2020. NIH Public Access, 2359
Wasifur Rahman, Md Kamrul Hasan, Sangwu Lee, Amir Zadeh, Chengfeng Mao, Louis-Philippe Morency, and Ehsan Hoque. 2020 · 2020
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Summarize before aggregate: a global-to-local heterogeneous graph inference network for conversational emotion recognition. In Proceedings of the 28th International Conference on Computational Linguistics . 4153–4163
Dongming Sheng, Dong Wang, Ying Shen, Haitao Zheng, and Haozhuang Liu. 2020 · 2020
Cited alongside, same era.
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Wenmeng Yu, Hua Xu, Fanyang Meng, Yilin Zhu, Yixiao Ma, Jiele Wu, Jiyun Zou, and Kaicheng Yang. 2020 · 2020
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