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

Showing 111120 of 141 papers

TitleStatusHype
Summarize before Aggregate: A Global-to-local Heterogeneous Graph Inference Network for Conversational Emotion Recognition0
SymantoResearch at SemEval-2019 Task 3: Combined Neural Models for Emotion Classification in Human-Chatbot Conversations0
TED: Turn Emphasis with Dialogue Feature Attention for Emotion Recognition in Conversation0
Topic-Driven and Knowledge-Aware Transformer for Dialogue Emotion Detection0
UniMEEC: Towards Unified Multimodal Emotion Recognition and Emotion Cause0
Watch the Speakers: A Hybrid Continuous Attribution Network for Emotion Recognition in Conversation With Emotion Disentanglement0
Dynamic Parameter Memory: Temporary LoRA-Enhanced LLM for Long-Sequence Emotion Recognition in ConversationCode0
Accumulating Word Representations in Multi-level Context Integration for ERC TaskCode0
ConSSED at SemEval-2019 Task 3: Configurable Semantic and Sentiment Emotion DetectorCode0
MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in ConversationsCode0
Show:102550
← PrevPage 12 of 15Next →

No leaderboard results yet.