Addressing visual impairments: Essential software requirements for image caption solutions.
Visually impaired individuals actively utilize devices like computers, tablets, and smartphones, due to advancements in screen reader technologies. Integrating freely available deep learning models, image captioning can further enhance these readers, providing an affordable assistive tech solution....
| Publicado en: | Assistive Technology Vol. 38; no. 4; pp. 284 - 300 |
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| Autores principales: | , , , |
| Formato: | pictorial research tables/charts Journal Article |
| Publicado: |
Taylor & Francis Ltd
2026
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=194805439&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 194805439 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 10400435 YVP jtl: Assistive Technology issn: 10400435 maglogo: Y pubinfo: dt: 2026 vid: 38 iid: 4 pid: 377 pub: Taylor & Francis Ltd place: Philadelphia, Pennsylvania artinfo: ui: 194805439 180547826 194805439 194805439 10.1080/10400435.2024.2413650 194805439 ppf: 284 ppct: 16 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Addressing visual impairments: Essential software requirements for image caption solutions. aug: au: Ferreira de Oliveira Neto, Rosalvo Almeida Rocha, Larissa Pereira de Carvalho Filho, Milton Argenton Ramos, Ricardo affil: Computer Engineering Department, Federal University of Vale do São Francisco, Juazeiro -Ba, Brazil sug: subj: Persons with Visual Disabilities Assistive Technology Devices Utilization Reading Software Evaluation Human Male Female Adolescence Adult Qualitative Studies Questionnaires Structured Interview Patient Preference Word Lists Cloud Computing Deep Learning Needs Assessment Thematic Analysis Adolescent: 13-18 years Adult: 19-44 years Male Female ab: Visually impaired individuals actively utilize devices like computers, tablets, and smartphones, due to advancements in screen reader technologies. Integrating freely available deep learning models, image captioning can further enhance these readers, providing an affordable assistive tech solution. This research outlines the critical software requirements necessary for image captioning tools to effectively serve this demographic. Two qualitative investigations were conducted to determine these requirements. An online survey was first conducted to identify the main preferences of visually impaired users in relation to audio descriptive software, with findings visualized using word clouds. A subsequent study evaluated the proficiency of existing deep learning captioning models in addressing these stipulated requirements. Emphasizing the need for comprehensive image data, the results highlighted three primary areas: 1) characteristics of individuals, 2) color specifics of objects, and 3) the overall context of images. The research indicates that current captioning tools are not entirely effective for the visually impaired. Based on the delineated requirements and suggested future research paths, there is potential for the development of improved image captioning systems, advancing digital accessibility for the visually impaired. pubtype: Academic Journal doctype: pictorial research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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