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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

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Showing 101–125 of 141 papers

TitleStatusHype
MONAH: Multi-Modal Narratives for Humans to analyze conversationsCode0
A Hierarchical Transformer with Speaker Modeling for Emotion Recognition in ConversationCode1
DialogXL: All-in-One XLNet for Multi-Party Conversation Emotion RecognitionCode1
An Iterative Emotion Interaction Network for Emotion Recognition in Conversations—0
HiTrans: A Transformer-Based Context- and Speaker-Sensitive Model for Emotion Detection in Conversations—0
Summarize before Aggregate: A Global-to-local Heterogeneous Graph Inference Network for Conversational Emotion Recognition—0
Relation-aware Graph Attention Networks with Relational Position Encodings for Emotion Recognition in ConversationsCode1
DialogueTRM: Exploring the Intra- and Inter-Modal Emotional Behaviors in the Conversation—0
COSMIC: COmmonSense knowledge for eMotion Identification in ConversationsCode2
Exploiting Unsupervised Data for Emotion Recognition in ConversationsCode1
Hierarchical Pre-training for Sequence Labelling in Spoken Dialog—0
Contextualized Emotion Recognition in Conversation as Sequence Tagging—0
BiERU: Bidirectional Emotional Recurrent Unit for Conversational Sentiment AnalysisCode0
Multi-Task Learning with Auxiliary Speaker Identification for Conversational Emotion Recognition—0
Multilogue-Net: A Context Aware RNN for Multi-modal Emotion Detection and Sentiment Analysis in ConversationCode1
Hierarchical Transformer Network for Utterance-level Emotion Recognition—0
Real-Time Emotion Recognition via Attention Gated Hierarchical Memory NetworkCode0
Conversational Transfer Learning for Emotion Recognition—0
Knowledge-Enriched Transformer for Emotion Detection in Textual ConversationsCode0
Neural Feature Extraction for Contextual Emotion Detection—0
DialogueGCN: A Graph Convolutional Neural Network for Emotion Recognition in ConversationCode1
Modeling both context- and speaker-sensitive dependence for emotion detection in multi-speaker conversations—0
Attention-based Modeling for Emotion Detection and Classification in Textual Conversations—0
ConSSED at SemEval-2019 Task 3: Configurable Semantic and Sentiment Emotion DetectorCode0
SNU IDS at SemEval-2019 Task 3: Addressing Training-Test Class Distribution Mismatch in Conversational ClassificationCode0
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