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Emotion Recognition in Conversation
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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. .
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Dynamic Parameter Memory: Temporary LoRA-Enhanced LLM for Long-Sequence Emotion Recognition in Conversation
BeMERC: Behavior-Aware MLLM-based Framework for Multimodal Emotion Recognition in Conversation
GatedxLSTM: A Multimodal Affective Computing Approach for Emotion Recognition in Conversations
AIMA at SemEval-2024 Task 10: History-Based Emotion Recognition in Hindi-English Code-Mixed Conversations
TED: Turn Emphasis with Dialogue Feature Attention for Emotion Recognition in Conversation
Dynamic Graph Neural ODE Network for Multi-modal Emotion Recognition in Conversation
CMATH: Cross-Modality Augmented Transformer with Hierarchical Variational Distillation for Multimodal Emotion Recognition in Conversation
Recent Trends of Multimodal Affective Computing: A Survey from NLP Perspective
NUS-Emo at SemEval-2024 Task 3: Instruction-Tuning LLM for Multimodal Emotion-Cause Analysis in Conversations
Beyond Silent Letters: Amplifying LLMs in Emotion Recognition with Vocal Nuances
Tracing Intricate Cues in Dialogue: Joint Graph Structure and Sentiment Dynamics for Multimodal Emotion Recognition
Masked Graph Learning with Recurrent Alignment for Multimodal Emotion Recognition in Conversation
BiosERC: Integrating Biography Speakers Supported by LLMs for ERC Tasks
MasonTigers at SemEval-2024 Task 10: Emotion Discovery and Flip Reasoning in Conversation with Ensemble of Transformers and Prompting
Efficient Long-distance Latent Relation-aware Graph Neural Network for Multi-modal Emotion Recognition in Conversations
Enhancing Emotion Recognition in Conversation through Emotional Cross-Modal Fusion and Inter-class Contrastive Learning
Revisiting Multi-modal Emotion Learning with Broad State Space Models and Probability-guidance Fusion
Revisiting Multimodal Emotion Recognition in Conversation from the Perspective of Graph Spectrum
Context-Aware Siamese Networks for Efficient Emotion Recognition in Conversation
Multi-Task Multi-Modal Self-Supervised Learning for Facial Expression Recognition
UniMEEC: Towards Unified Multimodal Emotion Recognition and Emotion Cause
Emotion-Anchored Contrastive Learning Framework for Emotion Recognition in Conversation
CKERC : Joint Large Language Models with Commonsense Knowledge for Emotion Recognition in Conversation
SemEval 2024 -- Task 10: Emotion Discovery and Reasoning its Flip in Conversation (EDiReF)
Curriculum Learning Meets Directed Acyclic Graph for Multimodal Emotion Recognition
TelME: Teacher-leading Multimodal Fusion Network for Emotion Recognition in Conversation
Joyful: Joint Modality Fusion and Graph Contrastive Learning for Multimodal Emotion Recognition
Qwen-Audio: Advancing Universal Audio Understanding via Unified Large-Scale Audio-Language Models
Accumulating Word Representations in Multi-level Context Integration for ERC Task
A Transformer-Based Model With Self-Distillation for Multimodal Emotion Recognition in Conversations
Efficient Cross-Task Prompt Tuning for Few-Shot Conversational Emotion Recognition
From Multilingual Complexity to Emotional Clarity: Leveraging Commonsense to Unveil Emotions in Code-Mixed Dialogues
Multimodal Prompt Transformer with Hybrid Contrastive Learning for Emotion Recognition in Conversation
InstructERC: Reforming Emotion Recognition in Conversation with Multi-task Retrieval-Augmented Large Language Models
Watch the Speakers: A Hybrid Continuous Attribution Network for Emotion Recognition in Conversation With Emotion Disentanglement
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