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Erschienen in:
2011 | OriginalPaper | Buchkapitel
Accessing Music Digital Libraries by Combining Semantic Tags and Audio Content
verfasst von : Riccardo Miotto, Nicola Orio
Erschienen in: Digital Libraries and Archives
Verlag: Springer Berlin Heidelberg
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An interesting problem in accessing music digital libraries is how to combine the information of different sources in order to improve the retrieval effectiveness. This paper introduces an approach to represent a collection of tagged songs through an hidden Markov model with the purpose to develop a system that merges in the same framework both acoustic similarity and semantic descriptions. The former provides content-based information on song similarity, the latter provides context-aware information about individual songs. Experimental results show how the proposed model leads to better performances than approaches that rank songs using both a single information source and a their linear combination.