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Emotion Recognition In Conversation On Cped

Metrics

Accuracy of Sentiment

Macro-F1 of Sentiment

Results

Performance results of various models on this benchmark

			Paper Title	Repository
BERT+AVG+MLP	51.50	48.02	CPED: A Large-Scale Chinese Personalized and Emotional Dialogue Dataset for Conversational AI
DialogXL	51.24	46.96	DialogXL: All-in-One XLNet for Multi-Party Conversation Emotion Recognition
bcLSTM	49.65	45.40	Context-Dependent Sentiment Analysis in User-Generated Videos	-
TextRCNN	49.13	37.95	Recurrent Convolutional Neural Networks for Text Classification	-
BERT_{utt}	48.96	45.18	BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
TextCNN	48.90	34.37	Convolutional Neural Networks for Sentence Classification
FastText	48.62	30.33	Bag of Tricks for Efficient Text Classification
DialogueRNN	48.57	44.11	DialogueRNN: An Attentive RNN for Emotion Detection in Conversations
EmoBERTa	48.09	44.60	EmoBERTa: Speaker-Aware Emotion Recognition in Conversation with RoBERTa
TextRNN	47.89	37.07	Recurrent Neural Network for Text Classification with Multi-Task Learning	-
DialogueGCN	47.69	45.12	DialogueGCN: A Graph Convolutional Neural Network for Emotion Recognition in Conversation

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