Dots to Dialogue: Enhancing Accessibility through Braille Image-to-Speech Conversion

Braille script serves as a fundamental medium of communication for individuals with visual impairments. However, its interpretation by non-experts poses a significant challenge, hindering inclusivity in education and daily interactions. This study proposes a system that leverages Convolutional Neural Networks (CNNs) and the Google Text-to-Speech (GTTS) library to translate Braille text into multilingual speech. This research addresses the challenge of Braille literacy among visually impaired individuals by developing a system that translates Braille text into multilingual speech. The proposed solution utilizes advanced CNNs for accurate Braille character recognition and integrates GTTS technology for real-time speech output. The results demonstrate a significant improvement in accessibility and communication for users, with an accuracy rate of 97.28% achieved using the AlexNet model.”

Authors

Institutions

Publication Details

Published
2025-02-05
DOI
https://doi.org/10.1109/idciot64235.2025.10915102
Citations
2
Primary Topic
Tactile and Sensory Interactions
Type
article
Field-Weighted Citation Impact
2.86
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Dots to Dialogue: Enhancing Accessibility through Braille Image-to-Speech Conversion

N. S. Manjushree, M Sirisha, B Shwetha, U Vachana et al.
2 citations
Tactile and Sensory Interactions
2.86
article

Dots to Dialogue: Enhancing Accessibility through Braille Image-to-Speech Conversion

N. S. Manjushree, M Sirisha, B Shwetha, U Vachana, Aditya Kadlimatti
article en
2 citations

Abstract

Braille script serves as a fundamental medium of communication for individuals with visual impairments. However, its interpretation by non-experts poses a significant challenge, hindering inclusivity in education and daily interactions. This study proposes a system that leverages Convolutional Neural Networks (CNNs) and the Google Text-to-Speech (GTTS) library to translate Braille text into multilingual speech. This research addresses the challenge of Braille literacy among visually impaired individuals by developing a system that translates Braille text into multilingual speech. The proposed solution utilizes advanced CNNs for accurate Braille character recognition and integrates GTTS technology for real-time speech output. The results demonstrate a significant improvement in accessibility and communication for users, with an accuracy rate of 97.28% achieved using the AlexNet model.”

International Institute of Information Technology Bangalore (IN)
Openalex Percentile: Top 11%
Tactile and Sensory Interactions
2.86
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.