Enhancing User Experience through Voice Assistant Integration with Content Management Systems
Safaa Salam Hatem,
Fahad Naim Nife and
Israa Majeed Alsaadi
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
References: View complete reference list from CitEc
Citations:
Downloads: (external link)
https://eu-opensci.org/index.php/compute/article/view/10325 Abstract page (text/html)
https://eu-opensci.org/index.php/compute/article/download/10325/14144 Full text (application/pdf)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
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
Access Statistics for this article
More articles in European Journal of Information Technologies and Computer Science from European Open Science
Bibliographic data for series maintained by Support Team ().