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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 111120 of 141 papers

TitleStatusHype
Hierarchical Pre-training for Sequence Labelling in Spoken Dialog0
Contextualized Emotion Recognition in Conversation as Sequence Tagging0
BiERU: Bidirectional Emotional Recurrent Unit for Conversational Sentiment AnalysisCode0
Multi-Task Learning with Auxiliary Speaker Identification for Conversational Emotion Recognition0
Multilogue-Net: A Context Aware RNN for Multi-modal Emotion Detection and Sentiment Analysis in ConversationCode1
Hierarchical Transformer Network for Utterance-level Emotion Recognition0
Real-Time Emotion Recognition via Attention Gated Hierarchical Memory NetworkCode0
Conversational Transfer Learning for Emotion Recognition0
Knowledge-Enriched Transformer for Emotion Detection in Textual ConversationsCode0
Neural Feature Extraction for Contextual Emotion Detection0
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