Dance Hit Song Prediction

Abstract

Record companies invest billions of dollars in new talent around the globe each year. Gaining insight into what actually makes a hit song would provide tremendous benefits for the music industry. In this research we tackle this question by focussing on the dance hit song classification problem. A database of dance hit songs from 1985 until 2013 is built, including basic musical features, as well as more advanced features that capture a temporal aspect. A number of different classifiers are used to build and test dance hit prediction models. The resulting best model has a good performance when predicting whether a song is a "top 10" dance hit versus a lower listed position.

References in corpus (1)

• Meta-song evaluation for chord recognition

Cited by in corpus (7)

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• Statistical Evolutionary Laws in Music Styles
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• Hit Song Prediction Based on Early Adopter Data and Audio Features
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