基于多视角解耦融合的多模态会话情感识别
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张婷婷,朱小飞
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Multi-view decoupled fusion for multimodal emotion recognition in conversation
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Tingting ZHANG,Xiaofei ZHU
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| 表 3 不同模型在MELD数据集上的性能对比结果 |
| Tab.3 Performance comparison of different models on MELD dataset |
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| 模型 | F1% | Acc% | W-F1% | | 中性 | 惊讶 | 悲伤 | 快乐 | 愤怒 | | DialogueRNN# | 76.97 | 47.69 | 20.41 | 50.92 | 45.52 | 60.31 | 57.66 | | MMGCN# | 76.33 | 48.15 | 26.74 | 53.02 | 46.09 | 60.42 | 58.31 | | CTNet# | 77.40 | 52.70 | 32.50 | 56.00 | 44.60 | 62.00 | 60.50 | | MM-DFN$ | 77.76 | 50.69 | 22.93 | 54.78 | 47.82 | 62.49 | 59.46 | | SCMM$ | — | — | — | — | — | — | 59.44 | | CMCF-SRNet$ | — | — | — | — | — | 62.80 | 62.30 | | MultiDAG$ | — | — | — | — | — | 64.41 | 64.00 | | FrameERC$ | 80.00 | 58.10 | 42.54 | 63.37 | 56.27 | 67.62 | 66.33 | | AdaIGN$ | 79.75 | 60.53 | 43.70 | 64.54 | 56.15 | 67.62 | 66.79 | | MDF | 79.86 | 59.03 | 44.84* | 64.60 | 57.63* | 68.06* | 66.92* |
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