Paper

Learning Emotion-discriminative Representations for Zero-Shot Cross-lingual Speech Emotion Recognition

arXiv:2606.06200v1 Announce Type: cross Abstract: Zero-shot cross-lingual speech emotion recognition (SER) remains challenging due to distribution mismatches across languages and the lack of emotion annotations in target language. Under such conditions, models trained solely on source-language data frequently suffer from degraded generalization when evaluated on unseen target languages. To address this limitation, we propose an emotion-discriminative representation learning method that integrates supervised contrastive learning and speaker adversarial learning. The contrastive learning promot…

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