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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 121130 of 141 papers

TitleStatusHype
Mimicking the Thinking Process for Emotion Recognition in Conversation with Prompts and ParaphrasingCode0
Deep Emotion Recognition in Textual Conversations: A SurveyCode0
Long-Short Distance Graph Neural Networks and Improved Curriculum Learning for Emotion Recognition in ConversationCode0
Knowledge-Enriched Transformer for Emotion Detection in Textual ConversationsCode0
SemEval 2024 -- Task 10: Emotion Discovery and Reasoning its Flip in Conversation (EDiReF)Code0
MONAH: Multi-Modal Narratives for Humans to analyze conversationsCode0
Integrating Recurrence Dynamics for Speech Emotion RecognitionCode0
BiERU: Bidirectional Emotional Recurrent Unit for Conversational Sentiment AnalysisCode0
Context-Dependent Sentiment Analysis in User-Generated VideosCode0
From Multilingual Complexity to Emotional Clarity: Leveraging Commonsense to Unveil Emotions in Code-Mixed DialoguesCode0
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