awesome-emotion-recognition-in-conversations
A comprehensive reading list for Emotion Recognition in Conversations
https://github.com/declare-lab/awesome-emotion-recognition-in-conversations
Last synced: 3 days ago
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ERC
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- DialogueCRN: Contextual Reasoning Networks for Emotion Recognition in Conversations
- MMGCN: Multimodal Fusion via Deep Graph Convolution Network for Emotion Recognition in Conversation
- Directed Acyclic Graph Network for Conversational Emotion Recognition
- COIN: Conversational Interactive Networks for Emotion Recognition in Conversation
- DialogXL: All-in-One XLNet for Multi-Party Conversation Emotion Recognition
- Quantum-inspired Neural Network for Conversational Emotion Recognition
- Contextual Augmentation of Pretrained Language Models for Emotion Recognition in Conversations
- CAN-GRU: a Hierarchical Model for Emotion Recognition in Dialogue
- DialogueTRM: Exploring the Intra- and Inter-Modal Emotional Behaviors in the Conversation
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- Conversational Transfer Learning for Emotion Recognition
- Knowledge Aware Emotion Recognition in Textual Conversations via Multi-Task Incremental Transformer
- Summarize before Aggregate: A Global-to-local Heterogeneous Graph Inference Network for Conversational Emotion Recognition
- An Iterative Emotion Interaction Network for Emotion Recognition in Conversations
- Multi-Task Learning with Auxiliary Speaker Identification for Conversational Emotion Recognition
- Analysis of Utterance Combinations for Emotion Recognition in Conversation
- An interaction-aware attention network for speech emotion recognition in spoken dialogs
- HiTrans: A Transformer-Based Context- and Speaker-Sensitive Model for Emotion Detection in Conversations
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- Real-Time Emotion Recognition via Attention Gated Hierarchical Memory Network
- Interactive double states emotion cell model for textual dialogue emotion prediction
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- Non-acted multi-view audio-visual dyadic interactions. Project non-verbal emotion recognition in dyadic scenarios and speaker segmentation
- Higru: Hierarchical gated recurrent units for utterance-level emotion recognition
- Adapted Dynamic Memory Network for Emotion Recognition in Conversation
- Domain adversarial learning for emotion recognition
- Towards Emotion-aided Multi-modal Dialogue Act Classification
- Detecting Topic-Oriented Speaker Stance in Conversational Speech
- A Self-Attentive Emotion Recognition Network
- Hierarchical Transformer Network for Utterance-Level Emotion Recognition
- Exploring Perception Uncertainty for Emotion Recognition in Dyadic Conversation and Music Listening
- A Novel Semantic Approach for Intelligent Response Generation using Emotion Detection Incorporating NPMI Measure
- HGFM: A Hierarchical Grained and Feature Model for Acoustic Emotion Recognition
- A Dialogical Emotion Decoder for Speech Motion Recognition in Spoken Dialog
- Multilogue-Net: A Context Aware RNN for Multi-modal Emotion Detection and Sentiment Analysis in Conversation
- Adapted Dynamic Memory Network for Emotion Recognition in Conversation
- Contextualized Emotion Recognition in Conversation as Sequence Tagging
- Different Contextual Window Sizes based RNNs for Multimodal Emotion Detection in Interactive Conversations
- Retrospective Loss: Looking Back to Improve Training of Deep Neural Networks
- Attention-based modeling for emotion detection and classification in textual conversations
- BiERU: Bidirectional Emotional Recurrent Unit for Conversational Sentiment Analysis
- An Effective Deep Learning Approach for Dialogue Emotion Recognition in Car-Hailing Platform
- LIRMM-advanse at SemEval-2019 Task 3: Attentive conversation modeling for emotion detection and classification
- ntuer at semeval-2019 task 3: Emotion classification with word and sentence representations in rcnn
- Coastal at semeval-2019 task 3: Affect classification in dialogue using attentive bilstms
- EPITA-ADAPT at SemEval-2019 Task 3: Detecting emotions in textual conversations using deep learning models combination
- Modeling both Context-and Speaker-Sensitive Dependence for Emotion Detection in Multi-speaker Conversations
- What a Dialogue! A Deep Neural Framework for Contextual Affect Detection
- Attentional Neural Network for Emotion Detection in Conversations with Speaker Influence Awareness
- Knowledge-Enriched Transformer for Emotion Detection in Textual Conversations
- PT-CoDE: Pre-trained Context-Dependent Encoder for Utterance-level Emotion Recognition
- EmotionX-IDEA: Emotion BERT – an Affectional Model for Conversation
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- Modeling both Intra- and Inter-modal Influence for Real-Time Emotion Detection in Conversations
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- Mutual Correlation Attentive Factors in Dyadic Fusion Networks for Speech Emotion Recognition
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- A Self-Attentive Emotion Recognition Network
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- A Self-Attentive Emotion Recognition Network
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- A Self-Attentive Emotion Recognition Network
- DialogueGCN: A Graph Convolutional Neural Network for Emotion Recognition in Conversation
- DialogueRNN: An Attentive RNN for Emotion Detection in Conversations
- Conversational Memory Network for Emotion Recognition in Dyadic Dialogue Videos
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- Context-Dependent Embedding Utterance Representations for Emotion Recognition in Conversations
- Fuzzy Fingerprinting Transformer Language-Models for Emotion Recognition in Conversations - IEEE 2023
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- A Self-Attentive Emotion Recognition Network
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- A Self-Attentive Emotion Recognition Network
- Adapted Dynamic Memory Network for Emotion Recognition in Conversation
- Different Contextual Window Sizes based RNNs for Multimodal Emotion Detection in Interactive Conversations
- An interaction-aware attention network for speech emotion recognition in spoken dialogs
- An Effective Deep Learning Approach for Dialogue Emotion Recognition in Car-Hailing Platform
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- A Self-Attentive Emotion Recognition Network
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- Retrospective Loss: Looking Back to Improve Training of Deep Neural Networks
- Attention-based modeling for emotion detection and classification in textual conversations
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- Knowledge Aware Emotion Recognition in Textual Conversations via Multi-Task Incremental Transformer
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- DialogXL: All-in-One XLNet for Multi-Party Conversation Emotion Recognition
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- What a Dialogue! A Deep Neural Framework for Contextual Affect Detection
- EmotionX-IDEA: Emotion BERT – an Affectional Model for Conversation
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- HiTrans: A Transformer-Based Context- and Speaker-Sensitive Model for Emotion Detection in Conversations
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- DialogueTRM: Exploring the Intra- and Inter-Modal Emotional Behaviors in the Conversation
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- Coastal at semeval-2019 task 3: Affect classification in dialogue using attentive bilstms
- Towards Emotion-aided Multi-modal Dialogue Act Classification
- Multilogue-Net: A Context Aware RNN for Multi-modal Emotion Detection and Sentiment Analysis in Conversation
- Higru: Hierarchical gated recurrent units for utterance-level emotion recognition
- EPITA-ADAPT at SemEval-2019 Task 3: Detecting emotions in textual conversations using deep learning models combination
- Contextual Augmentation of Pretrained Language Models for Emotion Recognition in Conversations
- CAN-GRU: a Hierarchical Model for Emotion Recognition in Dialogue
- Summarize before Aggregate: A Global-to-local Heterogeneous Graph Inference Network for Conversational Emotion Recognition
- An Iterative Emotion Interaction Network for Emotion Recognition in Conversations
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- Fuzzy Fingerprinting Transformer Language-Models for Emotion Recognition in Conversations - IEEE 2023
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- HAN-ReGRU: hierarchical attention network with residual gated recurrent unit for emotion recognition in conversation
- Real-Time Emotion Recognition via Attention Gated Hierarchical Memory Network
- Domain adversarial learning for emotion recognition
- BiERU: Bidirectional Emotional Recurrent Unit for Conversational Sentiment Analysis
- Multi-Task Learning with Auxiliary Speaker Identification for Conversational Emotion Recognition
- ntuer at semeval-2019 task 3: Emotion classification with word and sentence representations in rcnn
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Overviews
- Beneath the Tip of the Iceberg: Current Challenges and New Directions in Sentiment Analysis Research
- Emotion Recognition in Conversation: Research Challenges, Datasets, and Recent Advances
- Deep Emotion Recognition in Textual Conversations: A Survey
- Deep Emotion Recognition in Textual Conversations: A Survey
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Data Resources
- Storytelling with Dialogue: A Critical Role Dungeons and Dragons Dataset
- ScenarioSA: A Dyadic Conversational Database for Interactive Sentiment Analysis
- K-EmoCon, a multimodal sensor dataset for continuous emotion recognition in naturalistic conversations
- Emotional Dialogue Acts
- MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations
- Understanding emotions in text using deep learning and big data
- Emotionlines: An emotion corpus of multi-party conversations
- DailyDialog: A Manually Labelled Multi-turn Dialogue Dataset
- The semaine database: Annotated multimodal records of emotionally colored conversations between a person and a limited agent
- IEMOCAP: Interactive emotional dyadic motion capture database
- ScenarioSA: A Dyadic Conversational Database for Interactive Sentiment Analysis
- MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations
- MUStARD: Towards Multimodal Sarcasm Detection (An Obviously Perfect Paper)
- The semaine database: Annotated multimodal records of emotionally colored conversations between a person and a limited agent
- Emotionlines: An emotion corpus of multi-party conversations
- K-EmoCon, a multimodal sensor dataset for continuous emotion recognition in naturalistic conversations
- Storytelling with Dialogue: A Critical Role Dungeons and Dragons Dataset
- Emotional Dialogue Acts
- DailyDialog: A Manually Labelled Multi-turn Dialogue Dataset
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Contextual Sentiment Analysis
- Quantum-Inspired DMATT-BiGRU for Conversational Sentiment Analysis
- Quantum-Inspired DMATT-BiGRU for Conversational Sentiment Analysis
- Sentiment Forecasting in Dialog
- DCR-Net: A Deep Co-Interactive Relation Network for Joint Dialog Act Recognition and Sentiment Classification
- A Quantum-like Multimodal Network Framework for Modeling Interaction Dynamics in Multiparty Conversational Sentiment Analysis
- Quantum-Inspired Interactive Networks for Conversational Sentiment Analysis
- Quantum-Inspired DMATT-BiGRU for Conversational Sentiment Analysis
- Quantum-Inspired DMATT-BiGRU for Conversational Sentiment Analysis
- Quantum-Inspired DMATT-BiGRU for Conversational Sentiment Analysis
- Quantum-Inspired DMATT-BiGRU for Conversational Sentiment Analysis
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Contexutal Sarcasm Analysis
- Reactive Supervision: A New Method for Collecting Sarcasm Data
- Sarcasm Detection Using an Ensemble Approach
- Sarcasm Detection using Context Separators in Online Discourse
- C-Net: Contextual Network for Sarcasm Detection
- Sarcasm Identification and Detection in Conversion Context using BERT
- Applying Transformers and Aspect-based Sentiment Analysis approaches on Sarcasm Detection
- Neural Sarcasm Detection using Conversation Context
- Context-Aware Sarcasm Detection Using BERT
- Transformers on Sarcasm Detection with Context
- A Novel Hierarchical BERT Architecture for Sarcasm Detection
- Detecting Sarcasm in Conversation Context Using Transformer-Based Models
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Others
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Workshops and Shared Tasks