Abstract
Manual creation of music playlists is a time consuming task that is typically characterized by an individual listening for similar audio features among a number of songs. The goal of this project is to reduce the time spent in performing this task by achieving the following: given an arbitrary collection of digital music recordings, automatically sort songs with similar musical qualities into playlists. This problem statement can essentially be reduced to a clustering problem, and this is the approach that we take. In this project, we accomplish the automatic generation of playlists by combining the use of music analysis tools and clustering algorithms from the field of machine learning. Additionally, we incorporate various visualization tools into the application user interface in order to give users an intuitive representation of the resultant playlists.
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