# Apple — DiscoSign: Discourse-Aware Text to Sign Language Gloss Translation

- Company: Apple (apple.com)
- Announced: 2026-09-11
- Category: research-paper
- Coverage: not counted
- Announcement: yes
- Group: announcements
- Source: https://machinelearning.apple.com/research/discosign-gloss-translation
- Record: https://forck.live/items/10299-discosign-discourse-aware-text-to-sign-language-gloss-translation
- Subject: Machine Learning Research

Apple researchers introduce DiscoSign, a computational framework for discourse-aware text to sign language gloss translation that addresses spatial coreference resolution, question-answer clauses, and concept-gloss consistency using a modular large language model approach. The work establishes the first systematic framework for discourse-level text to sign language gloss translation with novel evaluation metrics designed to assess discourse coherence.

## Evidence

Verbatim from https://machinelearning.apple.com/research/discosign-gloss-translation:

> We introduce DiscoSign, a computational approach for discourse-aware text to sign language gloss translation grounded in linguistic research. We address three key phenomena within our modular Large Language Model (LLM)-based translation framework: (i) spatial coreference resolution, where entities maintain consistent spatial locations throughout discourse; (ii) Question-Answer Clauses (QACs), pseudocleft structures serving specific discourse functions; and (iii) concept-gloss consistency, ensuring stable mappings between English concepts and American Sign Language (ASL) signs.

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Record: https://forck.live/items/10299-discosign-discourse-aware-text-to-sign-language-gloss-translation
Catalogue: https://forck.live/llms.txt
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