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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 51–100 of 141 papers

TitleStatusHype
How to Enhance Causal Discrimination of Utterances: A Case on Affective ReasoningCode1
Context-Dependent Embedding Utterance Representations for Emotion Recognition in ConversationsCode0
HCAM -- Hierarchical Cross Attention Model for Multi-modal Emotion Recognition—0
EmotionIC: emotional inertia and contagion-driven dependency modeling for emotion recognition in conversationCode0
BERT-ERC: Fine-tuning BERT is Enough for Emotion Recognition in Conversation—0
Multivariate, Multi-Frequency and Multimodal: Rethinking Graph Neural Networks for Emotion Recognition in ConversationCode1
UniMSE: Towards Unified Multimodal Sentiment Analysis and Emotion RecognitionCode2
Deep Emotion Recognition in Textual Conversations: A SurveyCode0
Korean Drama Scene Transcript Dataset for Emotion Recognition in Conversations—0
Distribution-based Emotion Recognition in ConversationCode1
Supervised Prototypical Contrastive Learning for Emotion Recognition in ConversationCode1
DialogueEIN: Emotion Interaction Network for Dialogue Affective Analysis—0
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
Emotion Recognition in Conversation using Probabilistic Soft Logic—0
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
Static and Dynamic Speaker Modeling based on Graph Neural Network for Emotion Recognition in Conversation—0
The Emotion is Not One-hot Encoding: Learning with Grayscale Label for Emotion Recognition in ConversationCode1
Speaker-Guided Encoder-Decoder Framework for Emotion Recognition in Conversation—0
M2FNet: Multi-modal Fusion Network for Emotion Recognition in Conversation—0
MMDAG: Multimodal Directed Acyclic Graph Network for Emotion Recognition in Conversation—0
CPED: A Large-Scale Chinese Personalized and Emotional Dialogue Dataset for Conversational AICode2
EmotionFlow: Capture the Dialogue Level Emotion TransitionsCode1
M2R2: Missing-Modality Robust emotion Recognition framework with iterative data augmentation—0
COGMEN: COntextualized GNN based Multimodal Emotion recognitioNCode1
EmoCaps:Emotion Capsule based Model for Conversationl Emotion Recognition—0
EmoCaps: Emotion Capsule based Model for Conversational Emotion Recognition—0
MM-DFN: Multimodal Dynamic Fusion Network for Emotion Recognition in ConversationsCode1
Structure-Aware Transformer for Graph Representation LearningCode2
S+PAGE: A Speaker and Position-Aware Graph Neural Network Model for Emotion Recognition in Conversation—0
Hybrid Curriculum Learning for Emotion Recognition in Conversation—0
Contrast and Generation Make BART a Good Dialogue Emotion RecognizerCode1
A Discourse-Aware Graph Neural Network for Emotion Recognition in Multi-Party Conversation—0
Past, Present, and Future: Conversational Emotion Recognition through Structural Modeling of Psychological KnowledgeCode1
Knowledge-Interactive Network with Sentiment Polarity Intensity-Aware Multi-Task Learning for Emotion Recognition in Conversations—0
CoMPM: Context Modeling with Speaker's Pre-trained Memory Tracking for Emotion Recognition in Conversation—0
KNOT: Knowledge Distillation using Optimal Transport for Solving NLP TasksCode1
Few-Shot Emotion Recognition in Conversation with Sequential Prototypical NetworksCode1
EmoWOZ: A Large-Scale Corpus and Labelling Scheme for Emotion Recognition in Task-Oriented Dialogue SystemsCode0
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
Topic-Driven and Knowledge-Aware Transformer for Dialogue Emotion Detection—0
COIN: Conversational Interactive Networks for Emotion Recognition in Conversation—0
Directed Acyclic Graph Network for Conversational Emotion RecognitionCode1
Emotion Dynamics Modeling via BERT—0
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