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Geometric Second-Order Feature Correlation Learning for Self-Supervised Speech Emotion Recognition

Announce Type: new Abstract: Self-supervised learning (SSL) yields powerful, context-rich representations for speech emotion recognition (SER), yet aggregating these representations into holistic descriptors remains a bottleneck. Conventional first-order aggregation implicitly assumes feature independence, which overlooks the latent Riemannian geometry and discards higher-order relationships essential to the representational power of the backbone. To address this problem, this paper proposes...

arXiv CS 2d ago

Task-Vector Arithmetic for Emotional Expressivity Control in Language-Model-Based Text-to-Speech

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arXiv CS 5d ago