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Multi-Feature Speech Emotion Recognition Based on Improved Efficient Channel Attention Mechanism
DU Chenyang, ZHANG Xueying, HUANG Lixia, LI Juan
Computer Engineering
, 2025, 51(
4
): 97-106. DOI:
10.19678/j.issn.1000-3428.0069185
Table 8
Comparison of the proposed model with other models on CASIA
Other figure/table from this article
Fig.1
Multi-feature IECA-CTT network structure
Fig.2
ECA module structure
Fig.3
IECA module structure
Fig.4
TCN structure
Fig.5
Weight generation network
Table 1
IECA performance comparison experiment result
Fig.6
Box diagrams of different attention mechanisms on two datasets
Fig.7
t-SNE visualization of features on EMODB data
Table 2
Validity verification experiment result of dual-feature fusion
Table 3
Comparison experiment result of decision-level fusion strategies
Table 4
Emotion classification indicators on EMODB
Table 5
Emotion classification indicators on CASIA
Table 6
Final classification indicators of the proposed model
Fig.8
Confusion matrix of the model on EMODB
Fig.9
Confusion matrix of the model on CASIA
Table 7
Comparison of the proposed model with other models on EMODB