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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 26–50 of 141 papers

TitleStatusHype
GRASP: Guiding model with RelAtional Semantics using Prompt for Dialogue Relation ExtractionCode1
Contextual Information and Commonsense Based Prompt for Emotion Recognition in ConversationCode1
GA2MIF: Graph and Attention Based Two-Stage Multi-Source Information Fusion for Conversational Emotion DetectionCode1
GraphCFC: A Directed Graph Based Cross-Modal Feature Complementation Approach for Multimodal Conversational Emotion RecognitionCode1
CoMPM: Context Modeling with Speaker’s Pre-trained Memory Tracking for Emotion Recognition in ConversationCode1
The Emotion is Not One-hot Encoding: Learning with Grayscale Label for Emotion Recognition in ConversationCode1
EmotionFlow: Capture the Dialogue Level Emotion TransitionsCode1
COGMEN: COntextualized GNN based Multimodal Emotion recognitioNCode1
MM-DFN: Multimodal Dynamic Fusion Network for Emotion Recognition in ConversationsCode1
Contrast and Generation Make BART a Good Dialogue Emotion RecognizerCode1
Past, Present, and Future: Conversational Emotion Recognition through Structural Modeling of Psychological KnowledgeCode1
KNOT: Knowledge Distillation using Optimal Transport for Solving NLP TasksCode1
Few-Shot Emotion Recognition in Conversation with Sequential Prototypical NetworksCode1
Graph Based Network with Contextualized Representations of Turns in DialogueCode1
EmoBERTa: Speaker-Aware Emotion Recognition in Conversation with RoBERTaCode1
CoMPM: Context Modeling with Speaker's Pre-trained Memory Tracking for Emotion Recognition in ConversationCode1
MMGCN: Multimodal Fusion via Deep Graph Convolution Network for Emotion Recognition in ConversationCode1
DialogueCRN: Contextual Reasoning Networks for Emotion Recognition in ConversationsCode1
Directed Acyclic Graph Network for Conversational Emotion RecognitionCode1
A Hierarchical Transformer with Speaker Modeling for Emotion Recognition in ConversationCode1
DialogXL: All-in-One XLNet for Multi-Party Conversation Emotion RecognitionCode1
Relation-aware Graph Attention Networks with Relational Position Encodings for Emotion Recognition in ConversationsCode1
Exploiting Unsupervised Data for Emotion Recognition in ConversationsCode1
Multilogue-Net: A Context Aware RNN for Multi-modal Emotion Detection and Sentiment Analysis in ConversationCode1
DialogueGCN: A Graph Convolutional Neural Network for Emotion Recognition in ConversationCode1
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