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Emotion recognition can be significantly improved by adapting to individual expressive traits, with ML-SAN outperforming static models in capturing nuanced emotional expressions.
Unlock cross-lingual speech emotion recognition for low-resource languages with a new method that needs only 5 labeled examples.