Enhancing E-Commerce Accessibility Through a Novel Voice Assistant Approach for Web and Mobile Applications

As e-commerce platforms play a larger role in everyday transactions, it has grown important to ensure that users with disabilities can access them. This research introduces a new method for improving accessibility in web and mobile e-commerce applications by integrating intelligent voice assistants. The methodology utilizes natural language processing (NLP) together with machine learning techniques to facilitate navigation, product discovery, and transactions for people with visual, motor, or cognitive challenges. The system reduces the problems created by traditional graphical user interfaces (GUIs), which often restrict accessibility, by enabling users to interact with e-commerce platforms using voice commands. The study investigates the design of the voice assistant system, covering its combination with web and mobile applications, and assesses the advantages and disadvantages of voice interaction versus traditional input approaches. The user study investigates how the suggested solution performs and is usable, especially for the purpose of enhancing user experience for persons living with disabilities. The findings illustrate that the voice-based assistant greatly boosts accessibility, usability, and overall user satisfaction in multiple user groups. This research adds to the expanding literature on inclusive design for digital platforms, presenting insights into how voice technology might help close accessibility gaps in e-commerce. Future paths for improving voice interaction capabilities and broadening their use in other sectors are also part of the discussion.

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Publication Details

Published
2024-12-12
DOI
https://doi.org/10.1109/aicecs63354.2024.10956866
Citations
3
Primary Topic
AI in Service Interactions
Type
article
Field-Weighted Citation Impact
1.04
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article

Enhancing E-Commerce Accessibility Through a Novel Voice Assistant Approach for Web and Mobile Applications

Akshay Nagpal, Gaurav Mehta, Vivekananda Jayaram, Balaji Shesharao Ingole et al.
3 citations
AI in Service Interactions
1.04
article

Enhancing E-Commerce Accessibility Through a Novel Voice Assistant Approach for Web and Mobile Applications

Akshay Nagpal, Gaurav Mehta, Vivekananda Jayaram, Balaji Shesharao Ingole, Manjunatha Sughaturu Krishnappa, Amey Ram Banarse, Vishnu Ramineni
article en
3 citations

Abstract

As e-commerce platforms play a larger role in everyday transactions, it has grown important to ensure that users with disabilities can access them. This research introduces a new method for improving accessibility in web and mobile e-commerce applications by integrating intelligent voice assistants. The methodology utilizes natural language processing (NLP) together with machine learning techniques to facilitate navigation, product discovery, and transactions for people with visual, motor, or cognitive challenges. The system reduces the problems created by traditional graphical user interfaces (GUIs), which often restrict accessibility, by enabling users to interact with e-commerce platforms using voice commands. The study investigates the design of the voice assistant system, covering its combination with web and mobile applications, and assesses the advantages and disadvantages of voice interaction versus traditional input approaches. The user study investigates how the suggested solution performs and is usable, especially for the purpose of enhancing user experience for persons living with disabilities. The findings illustrate that the voice-based assistant greatly boosts accessibility, usability, and overall user satisfaction in multiple user groups. This research adds to the expanding literature on inclusive design for digital platforms, presenting insights into how voice technology might help close accessibility gaps in e-commerce. Future paths for improving voice interaction capabilities and broadening their use in other sectors are also part of the discussion.

Evans Analytical Group (United States) (US), TRC Companies (United States) (US)
Openalex Percentile: Top 18%
AI in Service Interactions
1.04
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