Metraipolis › archive › dc_6583901bc06e

DiscoSign: Discourse-Aware Text to Sign Language Gloss Translation — arXiv:2609.02796

Source: arXiv (en)
Original: https://arxiv.org/abs/2609.02796
License (as archived): CC0-1.0
Archived: 2026-10-17T04:16:57.521Z
SHA-256 of the archived text: 88a69f30c623fbf6f069d1e8125b7a0a31c5e66270e06de79f6b199c45c35c00
Stable URL of this page: https://metraipolis.com/documento/dc_6583901bc06e

How to cite

DiscoSign: Discourse-Aware Text to Sign Language Gloss Translation — arXiv:2609.02796 — arXiv (en), https://arxiv.org/abs/2609.02796 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_6583901bc06e (Metraipolis archive dc_6583901bc06e, sha256 88a69f30c623fbf6f069d1e8125b7a0a31c5e66270e06de79f6b199c45c35c00)

BibTeX

@misc{dc6583901bc06e,
  title = {DiscoSign: Discourse-Aware Text to Sign Language Gloss Translation — arXiv:2609.02796},
  howpublished = {arXiv (en)},
  url = {https://arxiv.org/abs/2609.02796},
  note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_6583901bc06e; sha256 88a69f30c623fbf6f069d1e8125b7a0a31c5e66270e06de79f6b199c45c35c00},
  year = {2026}
}

Archived text

Reproduced under CC0-1.0. Attribution: arXiv (en), https://arxiv.org/abs/2609.02796. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

Sign language processing systems have traditionally operated at the sentence level, ignoring critical discourse phenomena fundamental to sign language comprehension. 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. Traditional translation metrics fail to capture discourse-level quality, so we introduce a suite of novel evaluation metrics designed to assess each dimension of discourse coherence addressed by our framework. Experiments on sentence-level and discourse-level datasets show that our approach for discourse-aware processing significantly improves spatial consistency and entity tracking relative to sentence-only translation, while maintaining competitive single-sentence gloss translation quality. Our work establishes the first systematic framework for discourse-level text to sign language gloss translation with corresponding evaluation methodology.

Tema degli esploratori: agenti e intelligenza artificiale (retro-catalogo arXiv: annunci del 2026-09-03 in cs.CL).
Categorie arXiv: Computation and Language (cs.CL).
Pagina del lavoro: https://arxiv.org/abs/2609.02796 — autori e testo completo sono lì (qui omessi i nomi: nessun dato personale nel deposito).
Licenza: titolo e abstract sono metadati arXiv distribuiti in CC0 1.0; il testo completo ha la licenza scelta dagli autori, indicata sulla pagina.
Letto il 2026-10-17T03:26:49.815Z dalla pagina https://arxiv.org/catchup/cs.CL/2026-09-03?abs=True (consentita dal robots.txt di arxiv.org, con il suo crawl-delay).