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Towards an Automated System for Music Event Detection

November 30, 2018 ALL NEWS, CULTURE & PUBLIC, RESEARCH

Together with our partner we are currently working on the research project “RECAM”. This is a cooperation project between deecoob Technology GmbH and the Forensic Sience Investigation Lab at the University of Applied Sciences Mittweida, Germany. The abbreviation “RECAM” stands for retrospektive event monitoring for computer forensic enlightenment of copyright misuse on the basis of publicly available digital media. Our university partner has recently published a paper for the SEMAPRO 2018 conference: The Twelfth International Conference on Advances in Semantic Processing. The paper highlights some important results from the research project.

Announcements of events are regularly spread using the Internet, e.g., via online newspapers or social media. Often, these events involve playing music publicly that is protected by international copyright laws. Authorities entrusted with the protection of the artists’ interests have to find unregistered music events in order to fully exercise their duty. As a requirement, they need to find texts in the Internet that are related to such events like announcements or reports. However, event detection is a challenging task in the field of Text Mining due to the enormous variety of information that needs to be considered and the large amount of data that needs to be processed. Because no benchmark data is available for the domain of music event detection, in this paper a gold standard dataset is presented and made publicly available for further development and improvement. Subsequently, a process chain for the detection of music events incorporating external knowledge is proposed. Finally, the perfor- mance of three classification models is compared using various feature sets and two different datasets. The best performances reach an F1-measure of 0.94 and 0.946 for the classification of music and music event relevance, respectively.

Are you interested to learn more about this topic and read the paper? The full paper “Towards an Automated System for Music Event Detection” is available for reading and downloading.


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