Emotion Recognition In Conversation On Ec

Metrics

Micro-F1

Results

Performance results of various models on this benchmark

		Paper Title
NELEC	0.7765	NELEC at SemEval-2019 Task 3: Think Twice Before Going Deep
OUT2 + IN3 + USE + BERT	0.7731	SymantoResearch at SemEval-2019 Task 3: Combined Neural Models for Emotion Classification in Human-Chatbot Conversations
HRLCE + BERT	0.7709	ANA at SemEval-2019 Task 3: Contextual Emotion detection in Conversations through hierarchical LSTMs and BERT
ConSSED	0.7664	ConSSED at SemEval-2019 Task 3: Configurable Semantic and Sentiment Emotion Detector
Attention-based Modeling	0.7582	Attention-based Modeling for Emotion Detection and Classification in Textual Conversations
Oversampling	0.758	SNU IDS at SemEval-2019 Task 3: Addressing Training-Test Class Distribution Mismatch in Conversational Classification
DialogueRNN	0.758	Emotion Recognition in Conversation: Research Challenges, Datasets, and Recent Advances
KET	0.7413	Knowledge-Enriched Transformer for Emotion Detection in Textual Conversations
GRU + SVM	0.6993	Neural Feature Extraction for Contextual Emotion Detection

0 of 9 row(s) selected.

Emotion Recognition In Conversation On Ec | SOTA | HyperAI