Recent developments in artificial intelligence-based speech synthesis methods have changed how users access audio material in the fast-growing audiobook industry. The study develops an AI-based framework which creates customized audiobooks through user-specific voice cloning because people now demand tailored and immersive listening experiences. The proposed approach uses advanced deep learning models together with neural speech synthesis methods to extract vocal features from small voice samples and produce lifelike high-quality narration. The system generates audiobooks which maintain specific vocal characteristics of the user through tone and pitch and prosody differences which create an authentic emotional connection between the listener and the content. The speech generated by the system achieves high perceptual quality together with speaker similarity because the experimental results confirm the proposed architecture works effectively. The framework provides major advantages for educational purposes and assistive technologies and accessibility services through its ability to create customized learning experiences and restore voices. The current research develops an operational solution which enables users to create personalized audiobooks through their unique audio experiences because it incorporates contemporary trends in AI speech synthesis.