Sulaiman, Hamzah Asyrani and Mohammad Rizal, Nurul Najwa and Dolhalit, Mohamad Lutfi and Abdullasim, Nazreen and Che Ku Mohd, Che Ku Nuraini (2025) Enhancing academic repository accessibility through voice assistant integration. International Journal of Research and Innovation in Social Science (IJRISS), IX (VIII). pp. 1397-1406. ISSN 2454-6186
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Abstract
Digital repositories are vital tools in higher education, providing scholars with convenient access to a wide array of academic materials. However, most current search systems depend on rigid keyword-based queries and Boolean logic, which can be challenging for casual users, those with limited digital literacy, or individuals with disabilities. With advancements in speech recognition and natural language processing (NLP), voice assistants like Apple Siri, Google Assistant, and Amazon Alexa now enable users to interact with digital content through natural speech. This paper introduces a voice-enabled application specifically designed to enhance the search experience in academic repositories. The system leverages speech-to-text (STT) conversion to process spoken input, NLP to interpret user intent and expand queries, and retrieves relevant documents accordingly. A usability study involving 35 university students was conducted to evaluate system performance in terms of accessibility, effectiveness, and user satisfaction. The results revealed high satisfaction across all metrics, affirming that voice-based interfaces significantly improve the accessibility and usability of digital libraries. The paper also discusses current limitations and outlines directions for future research.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | Voice recognition, Natural language processing, Digital library, Accessibility, User experience. |
| Divisions: | Faculty of Information and Communication Technology > Department of Interactive Media |
| Depositing User: | Norfaradilla Idayu Ab. Ghafar |
| Date Deposited: | 11 Aug 2026 03:39 |
| Last Modified: | 11 Aug 2026 03:39 |
| URI: | http://eprints.utem.edu.my/id/eprint/30295 |
| Statistic Details: | View Download Statistic |
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