Towards Automatic Interpretation Of Statistical Graphs For The Visually Impaired

Figueroa-Gutierrez, Santiago; Montané-Jiménez, Luis G.; Arriaga, Juan Carlos Pérez; Rojano-Cáceres, José Rafael; Toledo-Toledo, Guadalupe

doi:10.1109/conisoft52520.2021.00033

Cited by 2 publications

(2 citation statements)

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“…Subsequently, they extracted keywords via the Frequent Pattern Growth algorithm to determine the optimal query for reformulation. Figueroa-Gutiérrez et al [27] proposed an architecture considering image processing techniques to automatically extract graphs under an image format, generating a description accessible to users with visual impairments. Meliones et al [28] used the augmented voice assistance of Alexa to allow elderly BUs to generate voice commands.…”

Section: Bu State-of-the-art Toolsmentioning

confidence: 99%

“…Approach Limitations [10] BUs face challenges due to lack of navigational support Reliance on third-party assistive tools [11] Utilization of screen readers, JAWS, voice assistants Limited effectiveness of assistive tools [20] Voice-activated email prototype Focused on a specific application (email) [21] Reduce cognitive load using summarized information Limited to information presented in tabular format [22][23][24] Leverage image processing to convert visual information Relies on image recognition; may not cover all content [25] Embed Near Field Connectivity (NFC) for interaction Limited to specific contexts (academic pages) [26] Pigeon algorithm for efficient web page retrieval Focused on improving search result relevancy [27] Image processing for automatic graph description Limited to content with graphical elements [28] Voice assistance augmentation for BUs Primarily extends voice assistant functionality…”

Section: Citedmentioning

confidence: 99%

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WSREB Mechanism: Web Search Results Exploration Mechanism for Blind Users

Naseer,

Rashid,

Saddal

et al. 2023

Applied Sciences

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In the contemporary digital landscape, web search functions as a pivotal conduit for information dissemination. Nevertheless, blind users (BUs) encounter substantial barriers in leveraging online services, attributable to intrinsic deficiencies in the information structure presented by online platforms. A critical analysis reveals that a considerable segment of BUs perceive online service access as either challenging or unfeasible, with only a fraction of search endeavors culminating successfully. This predicament stems largely from the linear nature of information interaction necessitated for BUs, a process that mandates sequential content relevancy assessment, consequently imposing cognitive strain and fostering information disorientation. Moreover, the prevailing evaluative metrics for web service efficacy—precision and recall—exhibit a glaring oversight of the nuanced behavioral and usability facets pertinent to BUs during search engine design. Addressing this, our study introduces an innovative framework to facilitate information exploration, grounded in the cognitive principles governing BUs. This framework, piloted using the Wikipedia dataset, seeks to revolutionize the search result space through categorical organization, thereby enhancing accessibility for BUs. Empirical and usability assessments, conducted on a cohort of legally blind individuals (N = 25), underscore the framework’s potential, demonstrating notable improvements in web content accessibility and system usability, with categorical accuracy standing at 84% and a usability quotient of 72.5%. This research thus holds significant promise for redefining web search paradigms to foster inclusivity and optimized user experiences for BUs.

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Section: Bu State-of-the-art Toolsmentioning

confidence: 99%