A Brief Review on Audiobook Recommendation System Based on Contextual and Emotional Cues

Vishakha Rajan Shinde and Dr. Arati Deshpande
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Vishakha Rajan Shinde: ME, Department of Computer Engineering Pune Institute of Computer Technology Dhankawadi, India
Dr. Arati Deshpande: Associate Professor, Department of Computer Engineering, Pune Institute of Computer Technology Dhankawadi, India

International Journal of Research and Innovation in Applied Science, 2025, vol. 10, issue 6, 1341-1345

Abstract: The exponential growth of audio book platforms has resulted in an overwhelming volume of content, necessitating intelligent recommendation systems that go beyond traditional filtering approaches. Conventional collaborative and content-based filtering methods often overlook critical aspects such as user emotions and real-time contextual factors, leading to suboptimal personalization. This survey presents a comprehensive review of recent developments in audio book recommendation systems that incorporate hybrid deep learning models, emotion recognition, and context- awareness. It evaluates various techniques, including sentiment analysis using natural language processing (NLP), collaborative-content hybridization, and multimodal emotion modeling. The paper also outlines the limitations of existing systems, such as the cold start problem, limited emotional input modalities, and privacy concerns. A detailed research gap analysis is conducted to highlight future opportunities in this domain. The survey aims to serve as a foundation for researchers and practitioners working toward emotionally adaptive,context-driven recommendation engines for audiobook and media platforms.

Date: 2025
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