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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 7180 of 141 papers

TitleStatusHype
Context-Aware Siamese Networks for Efficient Emotion Recognition in Conversation0
UniMEEC: Towards Unified Multimodal Emotion Recognition and Emotion Cause0
CKERC : Joint Large Language Models with Commonsense Knowledge for Emotion Recognition in Conversation0
SemEval 2024 -- Task 10: Emotion Discovery and Reasoning its Flip in Conversation (EDiReF)Code0
Accumulating Word Representations in Multi-level Context Integration for ERC TaskCode0
Efficient Cross-Task Prompt Tuning for Few-Shot Conversational Emotion Recognition0
From Multilingual Complexity to Emotional Clarity: Leveraging Commonsense to Unveil Emotions in Code-Mixed DialoguesCode0
Multimodal Prompt Transformer with Hybrid Contrastive Learning for Emotion Recognition in Conversation0
Watch the Speakers: A Hybrid Continuous Attribution Network for Emotion Recognition in Conversation With Emotion Disentanglement0
Fuzzy Fingerprinting Transformer Language-Models for Emotion Recognition in Conversations0
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