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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 1–25 of 141 papers

TitleStatusHype
Long-Short Distance Graph Neural Networks and Improved Curriculum Learning for Emotion Recognition in ConversationCode0
Dynamic Parameter Memory: Temporary LoRA-Enhanced LLM for Long-Sequence Emotion Recognition in ConversationCode0
BeMERC: Behavior-Aware MLLM-based Framework for Multimodal Emotion Recognition in Conversation—0
GatedxLSTM: A Multimodal Affective Computing Approach for Emotion Recognition in Conversations—0
AIMA at SemEval-2024 Task 10: History-Based Emotion Recognition in Hindi-English Code-Mixed Conversations—0
TED: Turn Emphasis with Dialogue Feature Attention for Emotion Recognition in Conversation—0
Dynamic Graph Neural ODE Network for Multi-modal Emotion Recognition in Conversation—0
CMATH: Cross-Modality Augmented Transformer with Hierarchical Variational Distillation for Multimodal Emotion Recognition in Conversation—0
Recent Trends of Multimodal Affective Computing: A Survey from NLP PerspectiveCode2
NUS-Emo at SemEval-2024 Task 3: Instruction-Tuning LLM for Multimodal Emotion-Cause Analysis in Conversations—0
Beyond Silent Letters: Amplifying LLMs in Emotion Recognition with Vocal NuancesCode1
Tracing Intricate Cues in Dialogue: Joint Graph Structure and Sentiment Dynamics for Multimodal Emotion RecognitionCode1
Masked Graph Learning with Recurrent Alignment for Multimodal Emotion Recognition in Conversation—0
BiosERC: Integrating Biography Speakers Supported by LLMs for ERC TasksCode1
MasonTigers at SemEval-2024 Task 10: Emotion Discovery and Flip Reasoning in Conversation with Ensemble of Transformers and Prompting—0
Efficient Long-distance Latent Relation-aware Graph Neural Network for Multi-modal Emotion Recognition in Conversations—0
FeedForward at SemEval-2024 Task 10: Trigger and sentext-height enriched emotion analysis in multi-party conversationsCode0
Enhancing Emotion Recognition in Conversation through Emotional Cross-Modal Fusion and Inter-class Contrastive Learning—0
Revisiting Multi-modal Emotion Learning with Broad State Space Models and Probability-guidance Fusion—0
Revisiting Multimodal Emotion Recognition in Conversation from the Perspective of Graph Spectrum—0
Context-Aware Siamese Networks for Efficient Emotion Recognition in Conversation—0
Multi-Task Multi-Modal Self-Supervised Learning for Facial Expression RecognitionCode1
UniMEEC: Towards Unified Multimodal Emotion Recognition and Emotion Cause—0
Emotion-Anchored Contrastive Learning Framework for Emotion Recognition in ConversationCode1
CKERC : Joint Large Language Models with Commonsense Knowledge for Emotion Recognition in Conversation—0
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