{"paper":{"title":"SymbolSight: Minimizing Inter-Symbol Interference for Reading with Prosthetic Vision","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"Optimizing symbol-to-letter assignments can reduce predicted confusion in prosthetic reading by a median factor of 22 across languages.","cross_cats":["cs.HC"],"primary_cat":"cs.CV","authors_text":"Jasmine Lesner, Michael Beyeler","submitted_at":"2026-01-24T06:14:02Z","abstract_excerpt":"Retinal prostheses restore limited visual perception, but low spatial resolution and temporal persistence make reading difficult. In sequential letter presentation, the afterimage of one symbol can interfere with perception of the next, leading to systematic recognition errors. Rather than relying on future hardware improvements, we investigate whether optimizing the visual symbols themselves can mitigate this temporal interference. We present SymbolSight, a computational framework that selects symbol-to-letter mappings to minimize confusion among frequently adjacent letters. Using simulated p"},"claims":{"count":4,"items":[{"kind":"strongest_claim","text":"Across simulations in Arabic, Bulgarian, and English, the resulting heterogeneous symbol sets reduced predicted confusion by a median factor of 22 relative to native alphabets.","source":"verdict.strongest_claim","status":"machine_extracted","claim_id":"C1","attestation":"unclaimed"},{"kind":"weakest_assumption","text":"The neural proxy observer and simulated prosthetic vision (SPV) provide a sufficiently accurate model of actual human letter confusability under real prosthetic conditions.","source":"verdict.weakest_assumption","status":"machine_extracted","claim_id":"C2","attestation":"unclaimed"},{"kind":"one_line_summary","text":"SymbolSight optimizes symbol-to-letter mappings via simulated prosthetic vision and bigram statistics, cutting predicted confusion by a median factor of 22 across Arabic, Bulgarian, and English.","source":"verdict.one_line_summary","status":"machine_extracted","claim_id":"C3","attestation":"unclaimed"},{"kind":"headline","text":"Optimizing symbol-to-letter assignments can reduce predicted confusion in prosthetic reading by a median factor of 22 across languages.","source":"verdict.pith_extraction.headline","status":"machine_extracted","claim_id":"C4","attestation":"unclaimed"}],"snapshot_sha256":"c7d84313d9117d87a029fea8bc215a2cca40cf919d8a170eb06591c4ca60e8db"},"source":{"id":"2601.17326","kind":"arxiv","version":2},"verdict":{"id":"fb77d411-fc99-496d-994a-b3f531128c11","model_set":{"reader":"grok-4.3"},"created_at":"2026-05-16T11:29:25.429078Z","strongest_claim":"Across simulations in Arabic, Bulgarian, and English, the resulting heterogeneous symbol sets reduced predicted confusion by a median factor of 22 relative to native alphabets.","one_line_summary":"SymbolSight optimizes symbol-to-letter mappings via simulated prosthetic vision and bigram statistics, cutting predicted confusion by a median factor of 22 across Arabic, Bulgarian, and English.","pipeline_version":"pith-pipeline@v0.9.0","weakest_assumption":"The neural proxy observer and simulated prosthetic vision (SPV) provide a sufficiently accurate model of actual human letter confusability under real prosthetic conditions.","pith_extraction_headline":"Optimizing symbol-to-letter assignments can reduce predicted confusion in prosthetic reading by a median factor of 22 across languages."},"references":{"count":28,"sample":[{"doi":"","year":2025,"title":"Subretinal Photovoltaic Implant to Restore Vision in Geographic Atrophy Due to AMD,","work_id":"ad76de5f-a351-432f-89fa-977b999e21a8","ref_index":1,"cited_arxiv_id":"","is_internal_anchor":false},{"doi":"","year":2011,"title":"Subretinal electronic chips allow blind patients to read letters and combine them to words,","work_id":"4977db88-2438-4763-ba17-832f76603023","ref_index":2,"cited_arxiv_id":"","is_internal_anchor":false},{"doi":"","year":2013,"title":"The Argus II epiretinal prosthesis system allows letter and word reading and long- term function in patients with profound vision loss,","work_id":"a3dcddd5-d2f7-4047-a85c-274d6766dd06","ref_index":3,"cited_arxiv_id":"","is_internal_anchor":false},{"doi":"","year":2017,"title":"Learning to see again: biological constraints on cortical plasticity and the implications for sight restoration technologies,","work_id":"573a459a-3d15-4ba7-9a69-e31e67212a3d","ref_index":4,"cited_arxiv_id":"","is_internal_anchor":false},{"doi":"","year":2024,"title":"Axonal stimulation affects the linear summation of single-point perception in three Argus II users,","work_id":"5b94c813-c75b-46d8-a08e-de654b1b7b77","ref_index":5,"cited_arxiv_id":"","is_internal_anchor":false}],"resolved_work":28,"snapshot_sha256":"cd2e54546da49eef2170946bd400865df0aab21d7646fca00b6393383ec057dd","internal_anchors":0},"formal_canon":{"evidence_count":2,"snapshot_sha256":"5942556cab4f13b0817bb41a4576397f266fb98002609acd51aa30c16e95b8d2"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"}