Context-Aware Background Music Recommendation System for Everyday Conversations Using Generative AI
Keywords:
Context-Aware Recommendation, Generative AI, Conversational BGM, Emotional Computing, Music RecommendationAbstract
With the increasing use of music software, many users prefer integrating
background music into everyday conversations to enhance emotional interaction.
However, traditional music recommendation systems fail to capture the subtle
contextual nuances of conversations in real-time for BGM recommendations. This
paper proposes a novel system that transcribes spoken dialogues into text and
leverages the contextual understanding capabilities of AI large models to match
conversation content with real-life interaction scenarios, recommending appropriate
BGMs from a curated dataset. In this way, the system provides dynamic BGM
recommendations for conversations, which not only enhance user immersion but also
open up new avenues for further exploring the role of AI in enhancing human
experiences through contextual music recommendations.
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Copyright (c) 2026 International Journal of Computer Science and Engineering
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