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SeRV: Semantic-Aligned Residual Vector Quantization for American Sign Language Generation
American Sign Language (ASL) generation remains challenging due to limited paired text-ASL motion data and the difficulty of learning motion representations both precise for reconstruction and predictable from linguistic input. Existing methods rely on motion tokenizers optimized for reconstruction,
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