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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 91100 of 141 papers

TitleStatusHype
EmoWOZ: A Large-Scale Corpus and Labelling Scheme for Emotion Recognition in Task-Oriented Dialogue SystemsCode0
Graph Based Network with Contextualized Representations of Turns in DialogueCode1
EmoBERTa: Speaker-Aware Emotion Recognition in Conversation with RoBERTaCode1
CoMPM: Context Modeling with Speaker's Pre-trained Memory Tracking for Emotion Recognition in ConversationCode1
MMGCN: Multimodal Fusion via Deep Graph Convolution Network for Emotion Recognition in ConversationCode1
DialogueCRN: Contextual Reasoning Networks for Emotion Recognition in ConversationsCode1
Topic-Driven and Knowledge-Aware Transformer for Dialogue Emotion Detection0
COIN: Conversational Interactive Networks for Emotion Recognition in Conversation0
Directed Acyclic Graph Network for Conversational Emotion RecognitionCode1
Emotion Dynamics Modeling via BERT0
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