The creation of huge databases coming from both restoration of existing analog archives and new content is demanding more and more reliable and fast tools for content analysis and description, to be used for searches, content queries and interactive access. In that context, musical genres are crucial descriptors since they have been widely used for years to organize music catalogues, libraries and music stores. Despite their use, musical genres remain a poorly defined concept, which make of the automatic classification problem a non-trivial task. In this article, we review the state-of-theart in automatic genre classification and present new directions in automatic organization of music collections.
The enormous growth of digital music databases has led to a comparable growth in the need for methods that help users organize and access such information. One area in particular that has seen much recent research activity is the use of automated techniques to describe audio content and to allow its identification, browsing and retrieval. This paper presents algorithms for audio content analysis, description and identification that are developed and implemented in the context of the AXMEDIS project.
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