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. Author manuscript; available in PMC: 2020 Apr 6.
Published in final edited form as: Proc AAAI Conf Artif Intell. 2018 Feb;2018:5642–5649.

Table 4:

Emotion recognition results on IEMOCAP test set using multimodal methods. Our model outperforms the previous baselines and the best scores are highlighted in bold.

Task Emotions Valence Arousal Dominance
Method A9 F1 MAE Corr MAE Corr MAE Corr
Majority 21.2 7.4 2.042 −0.02 1.352 0.01 1.331 0.17
SVM 24.1 18.0 0.251 0.06 0.546 0.54 0.687 0.42
RF 27.3 25.3 - - - - - -
THMM 23.5 10.8 - - - - - -
C-MKL 34.0 31.1 - - - - - -
EF-HCRF(⋆) 32.0(s) 20.5(s) - - - - - -
MV-HCRF(⋆) 32.0(s) 20.5(s) - - - - - -
DF 26.1 20.0 0.250 −0.04 0.613 0.27 0.726 0.09
EF-LSTM(⋆) 34.1(s) 32.3(s) 0.244(−) 0.09(−) 0.512(b) 0.62(−) 0.669(s) 0.51(sb)
MV-LSTM 31.3 26.7 0.257 0.02 0.513 0.62 0.668 0.52
BC-LSTM 35.9 34.1 0.248 0.07 0.593 0.40 0.733 0.32
TFN 36.0 34.5 0.251 0.04 0.521 0.55 0.671 0.43
MARN (no MAB) 31.2 28.0 0.246 0.09 0.509 0.63 0.679 0.44
MARN (no A) 23.0(3) 10.9(3) 0.249(5) 0.05(5) 0.609(4) 0.29(4) 0.752(4) 0.21(5)
MARN 37.0 (4) 35.9 (4) 0.242 (6) 0.10 (5) 0.497 (3) 0.65 (3) 0.655 (1) 0.50 (5)