Evaluation of AI-Based Speech Synthesis for Enhancing Learning Among Visually Impaired University Students: A Case Study of Bayero University, Kano (Gwale LGA, Kano State)
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- NGN 5000
Background of the Study
Visually impaired students face significant barriers in accessing learning materials in traditional educational settings. Textbooks, lecture notes, and online resources, which are predominantly text-based, pose challenges for these students (Nwachukwu et al., 2023). AI-based speech synthesis technologies, which convert written text into spoken words, offer a promising solution by enabling visually impaired students to access learning materials through auditory means (Ibrahim & Bello, 2024). By integrating speech synthesis tools into the academic environment, universities can improve accessibility, enhance the learning experience, and help visually impaired students participate more fully in their educational programs (Zubairu et al., 2025).
Bayero University, located in Gwale LGA, Kano State, offers an ideal case for examining the impact of AI-based speech synthesis on the learning outcomes of visually impaired students. The university has a growing number of visually impaired students who face challenges in accessing study materials. Implementing AI-based speech synthesis systems could provide these students with a more inclusive learning environment, helping them to engage more effectively with their coursework and lectures (Ali & Tanimu, 2023). This study seeks to evaluate the effectiveness of AI-based speech synthesis tools in enhancing the learning experience of visually impaired students at Bayero University, Kano.
Statement of the Problem
Visually impaired students at Bayero University, Kano, encounter challenges in accessing academic resources, which can affect their academic performance. Despite efforts to provide some accommodations, many students still struggle with reading and interacting with traditional learning materials. AI-based speech synthesis offers a potential solution by transforming written content into audio, but the effectiveness, user acceptance, and impact on academic performance need to be further explored. This study seeks to investigate how AI-based speech synthesis can enhance learning among visually impaired students at Bayero University.
Objectives of the Study
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To evaluate the effectiveness of AI-based speech synthesis in improving learning outcomes for visually impaired students at Bayero University, Kano.
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To assess the usability and accessibility of AI-based speech synthesis tools among visually impaired students at Bayero University.
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To examine the perceptions of students and faculty members regarding the integration of AI-based speech synthesis in supporting visually impaired learners.
Research Questions
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How effective is AI-based speech synthesis in improving learning outcomes for visually impaired students at Bayero University, Kano?
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What are the usability and accessibility challenges faced by visually impaired students when using AI-based speech synthesis tools?
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How do students and faculty members perceive the use of AI-based speech synthesis in supporting visually impaired learners at the university?
Significance of the Study
The study will contribute to the field of inclusive education by exploring the role of AI in enhancing learning opportunities for visually impaired students. It will provide valuable insights into the potential of speech synthesis technologies to create more accessible learning environments and support equal educational opportunities for all students, regardless of visual impairment.
Scope and Limitations of the Study
The study will focus on the evaluation of AI-based speech synthesis tools for visually impaired students at Bayero University, Kano, located in Gwale LGA, Kano State. The study will be limited to a sample of visually impaired students and their faculty members and will focus on the use of speech synthesis for academic learning materials.
Definitions of Terms
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Speech Synthesis: The process of converting written text into spoken language through the use of AI and machine learning technologies.
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Visually Impaired: Individuals who have partial or complete loss of vision, which limits their ability to read printed text without assistance.
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Inclusive Education: An educational approach that seeks to ensure equal access to learning opportunities for all students, including those with disabilities.
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