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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
COGMEN: COntextualized GNN based Multimodal Emotion recognitioNCode1
UniSA: Unified Generative Framework for Sentiment AnalysisCode1
CoMPM: Context Modeling with Speaker's Pre-trained Memory Tracking for Emotion Recognition in ConversationCode1
CoMPM: Context Modeling with Speaker’s Pre-trained Memory Tracking for Emotion Recognition in ConversationCode1
Conversational Memory Network for Emotion Recognition in Dyadic Dialogue Videos—0
A Discourse-Aware Graph Neural Network for Emotion Recognition in Multi-Party Conversation—0
A Dual-Stream Recurrence-Attention Network With Global-Local Awareness for Emotion Recognition in Textual Dialog—0
AIMA at SemEval-2024 Task 10: History-Based Emotion Recognition in Hindi-English Code-Mixed Conversations—0
An Iterative Emotion Interaction Network for Emotion Recognition in Conversations—0
Attention-based Modeling for Emotion Detection and Classification in Textual Conversations—0
BeMERC: Behavior-Aware MLLM-based Framework for Multimodal Emotion Recognition in Conversation—0
BERT-ERC: Fine-tuning BERT is Enough for Emotion Recognition in Conversation—0
CKERC : Joint Large Language Models with Commonsense Knowledge for Emotion Recognition in Conversation—0
CMATH: Cross-Modality Augmented Transformer with Hierarchical Variational Distillation for Multimodal Emotion Recognition in Conversation—0
COIN: Conversational Interactive Networks for Emotion Recognition in Conversation—0
CoMPM: Context Modeling with Speaker's Pre-trained Memory Tracking for Emotion Recognition in Conversation—0
Context-Aware Siamese Networks for Efficient Emotion Recognition in Conversation—0
Contextualized Emotion Recognition in Conversation as Sequence Tagging—0
DialogueEIN: Emotion Interaction Network for Dialogue Affective Analysis—0
DialogueTRM: Exploring the Intra- and Inter-Modal Emotional Behaviors in the Conversation—0
Dynamic Graph Neural ODE Network for Multi-modal Emotion Recognition in Conversation—0
Efficient Cross-Task Prompt Tuning for Few-Shot Conversational Emotion Recognition—0
Efficient Long-distance Latent Relation-aware Graph Neural Network for Multi-modal Emotion Recognition in Conversations—0
EmoCaps: Emotion Capsule based Model for Conversational Emotion Recognition—0
EmoCaps:Emotion Capsule based Model for Conversationl Emotion Recognition—0
Emotion Dynamics Modeling via BERT—0
Emotion Recognition in Conversation: Research Challenges, Datasets, and Recent Advances—0
Conversational Transfer Learning for Emotion Recognition—0
Emotion Recognition in Conversation using Probabilistic Soft Logic—0
Enhancing Emotion Recognition in Conversation through Emotional Cross-Modal Fusion and Inter-class Contrastive Learning—0
Fuzzy Fingerprinting Transformer Language-Models for Emotion Recognition in Conversations—0
GatedxLSTM: A Multimodal Affective Computing Approach for Emotion Recognition in Conversations—0
HCAM -- Hierarchical Cross Attention Model for Multi-modal Emotion Recognition—0
Hierarchical Pre-training for Sequence Labelling in Spoken Dialog—0
Hierarchical Transformer Network for Utterance-level Emotion Recognition—0
HiTrans: A Transformer-Based Context- and Speaker-Sensitive Model for Emotion Detection in Conversations—0
Hybrid Curriculum Learning for Emotion Recognition in Conversation—0
ICON: Interactive Conversational Memory Network for Multimodal Emotion Detection—0
Knowledge-Interactive Network with Sentiment Polarity Intensity-Aware Multi-Task Learning for Emotion Recognition in Conversations—0
Korean Drama Scene Transcript Dataset for Emotion Recognition in Conversations—0
M2FNet: Multi-modal Fusion Network for Emotion Recognition in Conversation—0
M2R2: Missing-Modality Robust emotion Recognition framework with iterative data augmentation—0
Masked Graph Learning with Recurrent Alignment for Multimodal Emotion Recognition in Conversation—0
MasonTigers at SemEval-2024 Task 10: Emotion Discovery and Flip Reasoning in Conversation with Ensemble of Transformers and Prompting—0
MMDAG: Multimodal Directed Acyclic Graph Network for Emotion Recognition in Conversation—0
Modeling both context- and speaker-sensitive dependence for emotion detection in multi-speaker conversations—0
Multimodal Prompt Transformer with Hybrid Contrastive Learning for Emotion Recognition in Conversation—0
Multi-Task Learning with Auxiliary Speaker Identification for Conversational Emotion Recognition—0
Neural Feature Extraction for Contextual Emotion Detection—0
NUS-Emo at SemEval-2024 Task 3: Instruction-Tuning LLM for Multimodal Emotion-Cause Analysis in Conversations—0
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