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Emotion Recognition in Conversation

Given the transcript of a conversation along with speaker information of each constituent utterance, the ERC task aims to identify the emotion of each utterance from several pre-defined emotions. Formally, given the input sequence of N number of utterances [(u1, p1), (u2, p2), . . . , (uN , pN )], where each utterance ui = [ui,1, ui,2, . . . , ui,T ] consists of T words ui,j and spoken by party pi, the task is to predict the emotion label ei of each utterance ui. .

Papers

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Showing 1–50 of 141 papers

TitleStatusHype
BERT: Pre-training of Deep Bidirectional Transformers for Language UnderstandingCode3
Qwen-Audio: Advancing Universal Audio Understanding via Unified Large-Scale Audio-Language ModelsCode3
Recent Trends of Multimodal Affective Computing: A Survey from NLP PerspectiveCode2
UniMSE: Towards Unified Multimodal Sentiment Analysis and Emotion RecognitionCode2
CPED: A Large-Scale Chinese Personalized and Emotional Dialogue Dataset for Conversational AICode2
Structure-Aware Transformer for Graph Representation LearningCode2
COSMIC: COmmonSense knowledge for eMotion Identification in ConversationsCode2
Bag of Tricks for Efficient Text ClassificationCode1
Past, Present, and Future: Conversational Emotion Recognition through Structural Modeling of Psychological KnowledgeCode1
Supervised Adversarial Contrastive Learning for Emotion Recognition in ConversationsCode1
Multi-Task Multi-Modal Self-Supervised Learning for Facial Expression RecognitionCode1
Multivariate, Multi-Frequency and Multimodal: Rethinking Graph Neural Networks for Emotion Recognition in ConversationCode1
MM-DFN: Multimodal Dynamic Fusion Network for Emotion Recognition in ConversationsCode1
Relation-aware Graph Attention Networks with Relational Position Encodings for Emotion Recognition in ConversationsCode1
GRASP: Guiding model with RelAtional Semantics using Prompt for Dialogue Relation ExtractionCode1
MMGCN: Multimodal Fusion via Deep Graph Convolution Network for Emotion Recognition in ConversationCode1
BiosERC: Integrating Biography Speakers Supported by LLMs for ERC TasksCode1
Tracing Intricate Cues in Dialogue: Joint Graph Structure and Sentiment Dynamics for Multimodal Emotion RecognitionCode1
EmoBERTa: Speaker-Aware Emotion Recognition in Conversation with RoBERTaCode1
GraphCFC: A Directed Graph Based Cross-Modal Feature Complementation Approach for Multimodal Conversational Emotion RecognitionCode1
Joyful: Joint Modality Fusion and Graph Contrastive Learning for Multimodal Emotion RecognitionCode1
COGMEN: COntextualized GNN based Multimodal Emotion recognitioNCode1
Beyond Silent Letters: Amplifying LLMs in Emotion Recognition with Vocal NuancesCode1
EmotionFlow: Capture the Dialogue Level Emotion TransitionsCode1
CoMPM: Context Modeling with Speaker’s Pre-trained Memory Tracking for Emotion Recognition in ConversationCode1
A Facial Expression-Aware Multimodal Multi-task Learning Framework for Emotion Recognition in Multi-party ConversationsCode1
GA2MIF: Graph and Attention Based Two-Stage Multi-Source Information Fusion for Conversational Emotion DetectionCode1
KNOT: Knowledge Distillation using Optimal Transport for Solving NLP TasksCode1
How to Enhance Causal Discrimination of Utterances: A Case on Affective ReasoningCode1
Emotion-Anchored Contrastive Learning Framework for Emotion Recognition in ConversationCode1
A Hierarchical Transformer with Speaker Modeling for Emotion Recognition in ConversationCode1
Contextual Information and Commonsense Based Prompt for Emotion Recognition in ConversationCode1
Exploiting Unsupervised Data for Emotion Recognition in ConversationsCode1
Contrast and Generation Make BART a Good Dialogue Emotion RecognizerCode1
Convolutional Neural Networks for Sentence ClassificationCode1
Few-Shot Emotion Recognition in Conversation with Sequential Prototypical NetworksCode1
GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash EquilibriumCode1
Curriculum Learning Meets Directed Acyclic Graph for Multimodal Emotion RecognitionCode1
CFN-ESA: A Cross-Modal Fusion Network with Emotion-Shift Awareness for Dialogue Emotion RecognitionCode1
DialogueCRN: Contextual Reasoning Networks for Emotion Recognition in ConversationsCode1
Graph Based Network with Contextualized Representations of Turns in DialogueCode1
DialogueGCN: A Graph Convolutional Neural Network for Emotion Recognition in ConversationCode1
DialogueRNN: An Attentive RNN for Emotion Detection in ConversationsCode1
InstructERC: Reforming Emotion Recognition in Conversation with Multi-task Retrieval-Augmented Large Language ModelsCode1
DialogXL: All-in-One XLNet for Multi-Party Conversation Emotion RecognitionCode1
Directed Acyclic Graph Network for Conversational Emotion RecognitionCode1
Distribution-based Emotion Recognition in ConversationCode1
A Transformer-Based Model With Self-Distillation for Multimodal Emotion Recognition in ConversationsCode1
CoMPM: Context Modeling with Speaker's Pre-trained Memory Tracking for Emotion Recognition in ConversationCode1
Multilogue-Net: A Context Aware RNN for Multi-modal Emotion Detection and Sentiment Analysis in ConversationCode1
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