{"type":"ScholarlyArticle","title":"A Gloss-driven Indian Sign Language Production System Using Learned Pose Representations","authors":[{"name":"Suvajit Patra","slug":"suvajit-patra","given":"Suvajit","family":"Patra","affiliation":""},{"name":"Arkadip Maitra","slug":"arkadip-maitra","given":"Arkadip","family":"Maitra","affiliation":""},{"name":"Swami Punyeshwarananda","slug":"swami-punyeshwarananda","given":"Swami","family":"Punyeshwarananda","affiliation":""},{"name":"Soumitra Samanta","slug":"soumitra-samanta","given":"Soumitra","family":"Samanta","affiliation":""}],"abstract":"Sign Language Production (SLP) system translates spoken or written language into sign language, enabling accessible communication between the deaf/hard-of-hearing and the hearing population. Being one of the most widely used sign languages globally, Indian Sign Language  (ISL) is a very low-resource language and lacks such SLP systems. This paper presents a scalable and modular SLP framework based on Sign-Pose-VQ-VAE model, designed for low-resource settings. The model learns discrete pose representations (codes) by disentangling body, left-hand, and right-hand keypoints, enabling efficient pose modeling and co-articulated sign generation. The proposed system is evaluated using a Hindi movie subtitle corpus coupled with an off-the-shelf back-translation model and achieves a gloss BLEU-4 score of 47.20. The system-generated signs are evaluated by certified ISL interpreters with an average rating of 4.33/5, and a BERT precision of 0.7683 on glosses. In addition, the proposed system achieves state-of-the-art performance among keypoint-based methods on the PHOENIX14T benchmark, attaining a BLEU-4 score of 10.03 and surpassing the previous best method by 0.67 points. The system with code is available at https://cs.rkmvu.ac.in/~isl/sl_gen_vqvae.","doi":"10.24963/ijcai.2026/823","url":"https://ijcai.org/proceedings/2026/823","pdf":"https://ijcai.org/proceedings/2026/0823.pdf","markdown":"https://ijcai.org/proceedings/2026/823.md","bibtex":"https://ijcai.org/proceedings/2026/bibtex/823","volume":{"slug":"2026","title":"Proceedings of the Thirty-Fifth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2026","url":"https://ijcai.org/proceedings/2026/","year":2026,"location":"Bremen, Germany","dates":"15-21 August 2026","editors":"Diego Calvanese","isbn":"978-1-956792-09-6","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2026"},"section":"AI and Social Good","track":"AI and Social Good","number":823,"pages":{"first":7399,"last":7407},"keywords":["Computer Vision: Computer Vision","Natural Language Processing: Natural Language Processing","Humans and AI: Humans and AI","Multidisciplinary Topics and Applications: Multidisciplinary Topics and Applications"],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}