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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 131140 of 141 papers

TitleStatusHype
DialogueRNN: An Attentive RNN for Emotion Detection in ConversationsCode1
BERT: Pre-training of Deep Bidirectional Transformers for Language UnderstandingCode3
MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in ConversationsCode0
ICON: Interactive Conversational Memory Network for Multimodal Emotion Detection0
Conversational Memory Network for Emotion Recognition in Dyadic Dialogue Videos0
Context-Dependent Sentiment Analysis in User-Generated VideosCode0
GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash EquilibriumCode1
Bag of Tricks for Efficient Text ClassificationCode1
Recurrent Neural Network for Text Classification with Multi-Task Learning0
Recurrent Convolutional Neural Networks for Text ClassificationCode0
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