Publication Details

Download

David Englmeier, Nina Hubig, Sebastian Goebl, Christian Böhm
Musical Similarity Analysis based on Chroma Features and Text Retrieval Methods
In Datenbanksysteme für Business, Technologie und Web (BTW 2015) - Workshopband. Bonn: Gesellschaft für Informatik e.V. Hamburg, Germany, March 2 - 6, 2015.

At the present day the world wide web is full of music. Highly effective algorithms for music compression and high data storage has made it easy to access all kind of music easily. However, it is not possible to look for a similar piece of music or a sound as easily as to google for a similar kind of text. Music is filtered by its title or artist. Although musicians can publish their compositions in a second, they will only be found by high youtube ratings or by market basket analysis. Less known artists need much luck to get heard, although their music might just be what people want to hear. To approach this issue, we propose a new framework called MIRA (Music Information Retrieval Application) foranalyzing audio files withexisting Information Retrieval (IR) methods. Textretrievalhasalreadyyieldedmanyhighlyefficientandgenerallyaccepted methods to assess the semantic distance of different text. We use these methods by translating music into equivalent audio words based on chroma features. We show that our framework can easily match music interpreted even by different artists.