The impact of AI-driven speech recognition tools on students’ library experience in University of Calabar Library, Cross River State
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- 1-5 Chapters
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- Table of Content: Available
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- NGN 5000
Background of the study
AI-driven speech recognition tools are emerging as innovative solutions to enhance accessibility and user interaction within library environments. At the University of Calabar Library, Cross River State, these tools are being deployed to facilitate a more interactive and inclusive user experience. By converting spoken language into text, speech recognition systems enable students to search for and access digital resources more efficiently, particularly benefiting users with disabilities or those who prefer auditory learning styles (Okoro, 2023). This technology also supports hands-free operation, thereby allowing students to multitask and engage with library resources in a more dynamic manner. Moreover, the integration of AI speech recognition enhances the overall accessibility of library services, contributing to improved satisfaction and engagement among the student population. Despite these advancements, challenges such as accuracy in diverse linguistic contexts, background noise interference, and system adaptability remain concerns that need to be addressed. This study investigates the impact of AI-driven speech recognition on the library experience at the University of Calabar, examining how it affects user satisfaction, resource accessibility, and overall academic performance (Ekem, 2024).
Statement of the problem
While AI-driven speech recognition tools hold significant potential to enhance library experiences, their implementation at University of Calabar Library faces several challenges. Issues including poor accuracy in accent recognition, interference from ambient noise, and the lack of robust user training impede the full realization of these benefits. Consequently, students may experience frustration and decreased reliance on library resources, which could affect academic performance. These challenges underscore the need for an in-depth evaluation of the current systems and potential improvements to optimize user experience (Okoro, 2023).
Objectives of the study
To assess the effectiveness of AI-driven speech recognition tools in the library setting.
To identify user challenges associated with these tools.
To propose recommendations for improving the accuracy and usability of speech recognition systems.
Research questions
How effective are AI-driven speech recognition tools in enhancing library services?
What challenges do students face when using these systems?
How can these tools be optimized for better user experiences?
Significance of the study
This study is significant as it examines the transformative impact of AI-driven speech recognition on enhancing student engagement and resource accessibility within the library. The findings will guide improvements in system design and user training, contributing to more inclusive and efficient library services (Okoro, 2023; Ekem, 2024).
Scope and limitations of the study
The study is confined to the evaluation of AI-driven speech recognition tools at University of Calabar Library, focusing on their impact on student experiences and resource accessibility.
Definitions of terms
Speech Recognition: Technology that converts spoken language into text.
User Accessibility: The ease with which users can access and benefit from library services.
Ambient Noise: Background sounds that may interfere with the performance of audio-based technologies.
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