Emotion Recognition In Conversation On Cped
평가 지표
Accuracy of Sentiment
Macro-F1 of Sentiment
평가 결과
이 벤치마크에서 각 모델의 성능 결과
비교 표
| 모델 이름 | Accuracy of Sentiment | Macro-F1 of Sentiment |
|---|---|---|
| recurrent-neural-network-for-text | 47.89 | 37.07 |
| bag-of-tricks-for-efficient-text | 48.62 | 30.33 |
| cped-a-large-scale-chinese-personalized-and-1 | 51.50 | 48.02 |
| dialogxl-all-in-one-xlnet-for-multi-party | 51.24 | 46.96 |
| recurrent-convolutional-neural-networks-for-2 | 49.13 | 37.95 |
| dialoguernn-an-attentive-rnn-for-emotion | 48.57 | 44.11 |
| bert-pre-training-of-deep-bidirectional | 48.96 | 45.18 |
| context-dependent-sentiment-analysis-in-user | 49.65 | 45.40 |
| dialoguegcn-a-graph-convolutional-neural | 47.69 | 45.12 |
| emoberta-speaker-aware-emotion-recognition-in | 48.09 | 44.60 |
| convolutional-neural-networks-for-sentence | 48.90 | 34.37 |