Personality Recognition in Conversation 벤치마크
Personality Recognition in Conversation on CPED
Accuracy (%)
- 2022-05-29 — BERT$_{ssenet}^{c}$: Accuracy (%) 67.25
| Rank | Model | Accuracy (%) | Macro-F1 | Accuracy of Neurotism | Accuracy of Extraversion | Accuracy of Openness | Accuracy of Agreeableness | Accuracy of Conscientiousness | Paper | Code | Year |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | BERT$_{ssenet}^{c}$ | 67.25 | 74.08 | 53.27 | 78.21 | 55.42 | 85.89 | 63.48 | CPED: A Large-Scale Chinese Personalized and Emotional Dialogue Dataset for Conversational AI | scutcyr/CPED | 2022 |
| 2 | BERT$^{s}$ | 67.23 | 72.93 | 50.75 | 78.08 | 57.93 | 85.76 | 63.60 | CPED: A Large-Scale Chinese Personalized and Emotional Dialogue Dataset for Conversational AI | scutcyr/CPED | 2022 |
| 3 | BERT$^{c}$ | 66.32 | 72.69 | 55.29 | 78.08 | 53.90 | 80.98 | 63.35 | CPED: A Large-Scale Chinese Personalized and Emotional Dialogue Dataset for Conversational AI | scutcyr/CPED | 2022 |
| 4 | BERT$_{senet}^{c}$ | 66.02 | 71.89 | 53.4 | 77.71 | 55.42 | 81.99 | 61.59 | CPED: A Large-Scale Chinese Personalized and Emotional Dialogue Dataset for Conversational AI | scutcyr/CPED | 2022 |