Machine Translation for Sign Languages

arXiv:2610.00881 · cs.CV · Submitted 2026-10-01 · Read on arXiv

cs.CV

Submitted: 2026-10-01

Updated: 2026-10-01

Terminology

• Machine Translation — 31× in this paper
• Benchmark — 8× in this paper · explained in 2 episodes
• Continuous Sign Language Recognition — 8× in this paper
• Transformer — 8× in this paper · explained in 2 episodes
• Alignment — 6× in this paper · explained in 1 episode
• Diffusion Model — 5× in this paper · explained in 8 episodes
• Generalization — 5× in this paper · explained in 13 episodes
• British Machine Vision Conference — 4× in this paper
• Transformer Architecture — 4× in this paper · explained in 2 episodes
• Core — 3× in this paper · explained in 2 episodes
• Feature Extraction — 3× in this paper · explained in 2 episodes
• Quantization — 3× in this paper · explained in 12 episodes
• Trace — 3× in this paper · explained in 2 episodes
• British Deaf Association — 2× in this paper
• Consistency — 2× in this paper · explained in 3 episodes
• Contrastive Learning — 2× in this paper · explained in 5 episodes
• Diffusion Models — 2× in this paper · explained in 6 episodes
• Distillation — 2× in this paper · explained in 2 episodes
• Grounding — 2× in this paper · explained in 3 episodes
• Isolated Sign Language Recognition — 2× in this paper
• Large Language Models (LLMs) — 2× in this paper · explained in 6 episodes
• Latent Representation — 2× in this paper · explained in 2 episodes
• Latent Representations — 2× in this paper · explained in 3 episodes
• Accountability — 1× in this paper · explained in 2 episodes
• Actor — 1× in this paper · explained in 3 episodes
• Adaptation — 1× in this paper · explained in 1 episode
• Attention Mechanism — 1× in this paper · explained in 3 episodes
• Convolutional Neural Networks (CNNs) — 1× in this paper · explained in 2 episodes
• Decoupling — 1× in this paper · explained in 2 episodes
• Domain Adaptation — 1× in this paper · explained in 5 episodes
• Dynamic Time Warping (DTW) — 1× in this paper · explained in 2 episodes
• Few-Shot Learning — 1× in this paper · explained in 4 episodes
• Fidelity — 1× in this paper · explained in 2 episodes
• Fine-Tuning — 1× in this paper · explained in 5 episodes
• Hybrid Architectures — 1× in this paper · explained in 3 episodes
• IEEE Spoken Language Technology Workshop — 1× in this paper
• Knowledge Distillation — 1× in this paper · explained in 11 episodes
• Motion Primitives — 1× in this paper · explained in 2 episodes
• Multimodal Dataset — 1× in this paper · explained in 2 episodes
• Provenance — 1× in this paper · explained in 4 episodes
• Pseudo-labels — 1× in this paper · explained in 2 episodes
• Representation Learning — 1× in this paper · explained in 2 episodes
• Self-Supervised Learning — 1× in this paper · explained in 8 episodes
• Semantic Alignment — 1× in this paper · explained in 3 episodes
• Support Vector Machines — 1× in this paper
• Tokenization — 1× in this paper · explained in 2 episodes
• Transfer Learning — 1× in this paper · explained in 10 episodes

Sources

• BBC-Oxford British Sign Language Dataset
• "Nothing about us without us": Perspectives of Global Deaf and Hard-of-hearing Community Members on Sign Language Technologies
• MS-ASL: A Large-Scale Data Set and Benchmark for Understanding American Sign Language
• LLaVA-SLT: Visual Language Tuning for Sign Language Translation
• MediaPipe: A Framework for Building Perception Pipelines
• A Tale of Two Languages: Large-Vocabulary Continuous Sign Language Recognition from Spoken Language Supervision

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