Naviblind: A multimodal AI assistant for visually impaired users to identify product information from images and speech

People with visual impairments often face significant challenges in identifying and accessing product information in their daily lives, particularly when visual cues such as packaging details, labels, or expiration dates are inaccessible. In this paper, we present NaviBlind, a multimodal AI-powered assistive system designed to help visually impaired individuals understand key product details through natural interactions. Our system combines image understanding using Gemini Flash vision models with Vietnamese speech recognition powered by PhoWhisper for extracting information needs directly from user voice commands. By uploading an image of the product and speaking what kind of information is needed, such as name, color, type, or expiry date, the system analyzes the image and returns a concise, structured textual description, which is then converted into Vietnamese speech. To ensure reliability, we incorporate mechanisms to detect uncertain or hallucinated outputs from the vision model, especially in cases of low-quality images. The system is deployed as a user-friendly web application, enabling real-time accessibility for users with limited visual capabilities. Experimental evaluation demonstrates the potential of NaviBlind in promoting autonomy and independence for the visually impaired in everyday shopping and product recognition tasks.

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Publication Details

Journal
CTU Journal of Innovation and Sustainable Development
Published
2025-10-16
DOI
https://doi.org/10.22144/ctujoisd.2025.057
Primary Topic
Tactile and Sensory Interactions
Type
article
Field-Weighted Citation Impact
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article

Naviblind: A multimodal AI assistant for visually impaired users to identify product information from images and speech

Minh-Anh Nguyen, Minh–Quan Tran, Dinh Thanh Son Le, Duy Truong et al.
CTU Journal of Innovation and Sustainable Development
Tactile and Sensory Interactions
article

Naviblind: A multimodal AI assistant for visually impaired users to identify product information from images and speech

Minh-Anh Nguyen, Minh–Quan Tran, Dinh Thanh Son Le, Duy Truong, D.-T. Pham
article en

Abstract

People with visual impairments often face significant challenges in identifying and accessing product information in their daily lives, particularly when visual cues such as packaging details, labels, or expiration dates are inaccessible. In this paper, we present NaviBlind, a multimodal AI-powered assistive system designed to help visually impaired individuals understand key product details through natural interactions. Our system combines image understanding using Gemini Flash vision models with Vietnamese speech recognition powered by PhoWhisper for extracting information needs directly from user voice commands. By uploading an image of the product and speaking what kind of information is needed, such as name, color, type, or expiry date, the system analyzes the image and returns a concise, structured textual description, which is then converted into Vietnamese speech. To ensure reliability, we incorporate mechanisms to detect uncertain or hallucinated outputs from the vision model, especially in cases of low-quality images. The system is deployed as a user-friendly web application, enabling real-time accessibility for users with limited visual capabilities. Experimental evaluation demonstrates the potential of NaviBlind in promoting autonomy and independence for the visually impaired in everyday shopping and product recognition tasks.

CTU Journal of Innovation and Sustainable DevelopmentVol. 17(Special issue: ISDS)
LinkedIn (United States) (US), Saigon Technology University (VN), Ho Chi Minh City University of Technology and Engineering (VN), Ho Chi Minh City University of Technology (VN)
Openalex Percentile: Top 71%
Tactile and Sensory Interactions
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Naviblind: A multimodal AI assistant for visually impaired users to identify product information from images and speech — Minh-Anh Nguyen, Minh–Quan Tran, et al. · CTU Journal of Innovation and Sustainable Development (2025) | TGRS Research Map | TGRS