Enhancing User Experience through Voice Assistant Integration with Content Management Systems

Safaa Salam Hatem, Fahad Naim Nife and Israa Majeed Alsaadi
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Safaa Salam Hatem: Al-Muthanna University, Iraq
Fahad Naim Nife: Al-Muthanna University, Iraq
Israa Majeed Alsaadi: Al-Muthanna University, Iraq

European Journal of Information Technologies and Computer Science, 2026, vol. 6, issue 1, 1-12

Abstract: Voice-based interfaces integrated into content management systems (CMSs) represent a feasible way to achieve more accessible digital publishing; however, while voice-enabled technologies are gaining widespread adoption, there is a lack of evidence on the effectiveness of voice interfaces for users who encounter difficulties using the traditional keyboard-and-mouse interaction paradigm. This study proposes and evaluates a voice-controlled WordPress interface for users with different accessibility needs, focusing on users with motor impairments, visual impairments (low vision), and limited computer literacy, and a pilot study with five participants (N= 5) compared the proposed voice interface to a standard input method in a within-subjects experimental design. The system was developed using the Google Voice Assistant, Dialogflow, and the WordPress REST API to enable end-to-end voice-driven content creation and management, and the results show that, although the voice interface led to a 22% increase in the average task completion time (M= 185.8 s vs. 152.4 s), it significantly reduced text entry errors by 77% (M= 2.6 vs. 11.2 errors). Participants also reported higher satisfaction with the voice-based system (M= 6.2/7 vs. 3.4/7 on the SEQ scale), and the results suggest that voice-controlled CMS interfaces may enhance accessibility and overall user experience while providing a validated and replicable framework for inclusive digital publishing.

Keywords: Accessibility; content management systems; user experience; voice assistants (search for similar items in EconPapers)
Date: 2026
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Persistent link: https://EconPapers.repec.org/RePEc:epw:comput:v:6:y:2026:i:1:id:10325

DOI: 10.24018/compute.2026.6.1.10325

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