An improved ECAPA-TDNN using multiscale channel attention and differential attention reports 82.20 percent accuracy on six-class infant cry emotion recognition on the iFLYTEK/USTC public dataset.
Dunstan’s theory identifies primal, reflexive vocalizations in infants aged 0-3 months linked to specific physiological needs, verified in later studies [1]
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Infant Cry Emotion Recognition Using Improved ECAPA-TDNN with Multiscale Feature Fusion and Attention Enhancement
An improved ECAPA-TDNN using multiscale channel attention and differential attention reports 82.20 percent accuracy on six-class infant cry emotion recognition on the iFLYTEK/USTC public dataset.