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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 4150 of 141 papers

TitleStatusHype
ERNetCL: A novel emotion recognition network in textual conversation based on curriculum learning strategy0
Revisiting Disentanglement and Fusion on Modality and Context in Conversational Multimodal Emotion Recognition0
CFN-ESA: A Cross-Modal Fusion Network with Emotion-Shift Awareness for Dialogue Emotion RecognitionCode1
FATRER: Full-Attention Topic Regularizer for Accurate and Robust Conversational Emotion RecognitionCode0
A Dual-Stream Recurrence-Attention Network With Global-Local Awareness for Emotion Recognition in Textual Dialog0
A Facial Expression-Aware Multimodal Multi-task Learning Framework for Emotion Recognition in Multi-party ConversationsCode1
Mimicking the Thinking Process for Emotion Recognition in Conversation with Prompts and ParaphrasingCode0
Supervised Adversarial Contrastive Learning for Emotion Recognition in ConversationsCode1
Speech-Text Dialog Pre-training for Spoken Dialog Understanding with Explicit Cross-Modal Alignment0
How to Enhance Causal Discrimination of Utterances: A Case on Affective ReasoningCode1
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