SOTAVerified

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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 131–140 of 141 papers

TitleStatusHype
Conversational Transfer Learning for Emotion Recognition—0
BERT-ERC: Fine-tuning BERT is Enough for Emotion Recognition in Conversation—0
Fuzzy Fingerprinting Transformer Language-Models for Emotion Recognition in Conversations—0
Emotion Recognition in Conversation: Research Challenges, Datasets, and Recent Advances—0
Emotion Dynamics Modeling via BERT—0
GatedxLSTM: A Multimodal Affective Computing Approach for Emotion Recognition in Conversations—0
EmoCaps:Emotion Capsule based Model for Conversationl Emotion Recognition—0
EmoCaps: Emotion Capsule based Model for Conversational Emotion Recognition—0
Efficient Long-distance Latent Relation-aware Graph Neural Network for Multi-modal Emotion Recognition in Conversations—0
HCAM -- Hierarchical Cross Attention Model for Multi-modal Emotion Recognition—0
Show:102550
← PrevPage 14 of 15Next →

No leaderboard results yet.