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Emotion Recognition In Conversation On Cped

Métriques

Accuracy of Sentiment

Macro-F1 of Sentiment

Résultats

Résultats de performance de divers modèles sur ce benchmark

Nom du modèle	Accuracy of Sentiment	Macro-F1 of Sentiment	Paper Title	Repository
TextRNN	47.89	37.07	Recurrent Neural Network for Text Classification with Multi-Task Learning	-
FastText	48.62	30.33	Bag of Tricks for Efficient Text Classification
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
TextRCNN	49.13	37.95	Recurrent Convolutional Neural Networks for Text Classification
DialogueRNN	48.57	44.11	DialogueRNN: An Attentive RNN for Emotion Detection in Conversations
BERT_{utt}	48.96	45.18	BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
bcLSTM	49.65	45.40	Context-Dependent Sentiment Analysis in User-Generated Videos
DialogueGCN	47.69	45.12	DialogueGCN: A Graph Convolutional Neural Network for Emotion Recognition in Conversation
EmoBERTa	48.09	44.60	EmoBERTa: Speaker-Aware Emotion Recognition in Conversation with RoBERTa
TextCNN	48.90	34.37	Convolutional Neural Networks for Sentence Classification

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