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Two-stage multiple instance learning networks with attention-based hybrid aggregation for speech emotion recognition | Synapse
March 3, 2026
Two-stage multiple instance learning networks with attention-based hybrid aggregation for speech emotion recognition
SZ
Shu Zhang
Okinawa Institute of Science and Technology Graduate University
CC
Chen Chen
New York State Department of Transportation
DW
Dandan Wang
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Puntos clave
The model achieves significant accuracy gains in speech emotion recognition tasks, pointing towards a more reliable system.
An accuracy boost of over 10% was observed compared to traditional methods, enhancing emotion detection.
Analysis based on a two-stage multiple-instance learning model utilizing attention mechanisms for better performance.
This approach may enable more robust emotion recognition in real-world applications, emphasizing the need for further testing.
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Zhang et al. (Tue,) studied this question.
synapsesocial.com/papers/69a7605dc6e9836116a2d094
https://doi.org/https://doi.org/10.1016/j.csl.2026.101946
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