Enhancing E-Commerce Accessibility Through a Novel Voice Assistant Approach for Web and Mobile Applications
Vishnu Ramineni, Balaji Shesharao Ingole, Vivekananda Jayaram, Gaurav Mehta, Manjunatha Sughaturu Krishnappa, Akshay Nagpal, Amey Ram Banarse · 2024
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.