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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM61902
Volume:
10 |
4 |
April 2026
Pages:
1-3
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Computer Science and Engineering
RKGIT
Computer Science and Engineering
RKGIT
NeoShop is a voice-enabled e-commerce web application developed using the MERN stack to simplify user interaction with online shopping platforms. The system integrates browser-based speech recognition to allow users to navigate, search, and perform actions through simple voice commands instead of relying entirely on traditional click-based interfaces. A rule-based logic engine processes spoken input and maps it to application routes, enabling fast and predictable responses without external AI dependencies. The backend, built with Node.js and Express, manages product data, authentication, and order processing, while MongoDB stores dynamic user and product information. During implementation, the system showed reduced interaction time for common tasks like opening the cart or searching products. In situations where users are multitasking or unable to use touch input, voice navigation proved noticeably useful. The overall design keeps performance lightweight while improving accessibility, especially for users who struggle with complex menus. The project demonstrates that practical, browser-native solutions can enhance user experience without adding unnecessary system complexity.
KEYWORDS
The development of NeoShop provided a practical look at how small changes in interaction design can impact overall usability. Instead of focusing only on adding features, the project explored how users move through an application and where friction exists. One clear observation during implementation was that even simple actions, like navigating to the cart or checking orders, often require multiple steps in traditional systems. Reducing that effort became a central idea behind the voice-enabled approach. The integration of a voice module using the Web Speech API turned out to be more effective than expected for controlled commands. Since the system uses a rule-based mapping instead of complex Natural Language Processing, it avoids unnecessary processing overhead and remains responsive. There were some limitations, especially when speech input was unclear or when background noise affected recognition, but within defined conditions, the system performed reliably. It felt more like a practical feature rather than an experimental one. From a system design perspective, the MERN stack architecture helped maintain a clean separation between components. The frontend handled interaction and state management, while the backend managed logic and data operations. This separation made testing easier, particularly when debugging issues related to API responses or voice-triggered navigation. In a few cases, backend delays did not affect the frontend experience significantly, which showed that the architecture handled failures reasonably well. In real-world scenarios, such as browsing while multitasking or using a device with limited accessibility, the benefit of voice navigation becomes more noticeable. It does not replace the graphical interface but complements it. That balance is important, because not all users will prefer voice interaction all the time. There is still scope for improvement. The system currently supports only a fixed set of commands and lacks adaptability to more natural language variations. Expanding this with better intent recognition or multi-language support could make it more flexible. Even with these limitations, the project demonstrates that effective user experience improvements do not always require complex or heavy AI solutions. Sometimes, using existing technologies in a thoughtful way is enough to make the system more intuitive and usable.
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Publication Date
4/29/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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The authors declare no conflict of interest related to this research work.
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