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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

Showing 101110 of 141 papers

TitleStatusHype
An Iterative Emotion Interaction Network for Emotion Recognition in Conversations0
Conversational Memory Network for Emotion Recognition in Dyadic Dialogue Videos0
Multimodal Prompt Transformer with Hybrid Contrastive Learning for Emotion Recognition in Conversation0
Multi-Task Learning with Auxiliary Speaker Identification for Conversational Emotion Recognition0
Contextualized Emotion Recognition in Conversation as Sequence Tagging0
Context-Aware Siamese Networks for Efficient Emotion Recognition in Conversation0
AIMA at SemEval-2024 Task 10: History-Based Emotion Recognition in Hindi-English Code-Mixed Conversations0
Neural Feature Extraction for Contextual Emotion Detection0
NUS-Emo at SemEval-2024 Task 3: Instruction-Tuning LLM for Multimodal Emotion-Cause Analysis in Conversations0
CoMPM: Context Modeling with Speaker's Pre-trained Memory Tracking for Emotion Recognition in Conversation0
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