Gloss Translation

Gloss translation focuses on converting spoken or written language into a simplified, intermediary representation (gloss) often used for sign language or multimodal data alignment. Current research emphasizes developing robust gloss-free methods, leveraging large language models (LLMs) and self-supervised learning to reduce reliance on scarce and costly gloss annotations, and exploring novel architectures like transformers and diffusion models for improved accuracy and efficiency in tasks such as sign language translation and production. This work has significant implications for bridging communication gaps for deaf and hard-of-hearing communities and advancing multimodal understanding in various domains, particularly low-resource language processing.