Enriching music mood annotation by semantic association reasoning

Mood annotation of music is challenging as it concerns not only audio content but also extra-musical information. It is a representative research topic about how to traverse the wellknown semantic gap. In this paper, we propose a new music-mood-specific ontology. Novel ontology-based semantic reasoning methods are applied to effectively bridge content-based information with web-based resources. Also, the system can automatically discover closely relevant semantics for music mood and thus a novel weighting method is proposed for mood propagation. Experiments show that the proposed method outperforms purely contentbased methods and significantly enhances the mood prediction accuracy. Furthermore, evaluations show the system's accuracy could be promisingly increased with the enrichment of metadata. Keywords-- Social music, Mood, Semantic reasoning, Ontology, Annotation

• Type: Conference
• Year: 2010
• Where: ICMCS
• Authors: Jun Wang, Xavier Anguera, Xiaoou Chen, Deshun Yang
• Keywords: ICMCS 2010, Mood Annotation, Multimedia, Semantic Reasoning, Wellknown Semantic Gap