Generating Similarity-based Playlists Using Traveling Salesman Algorithms
Sprache des Vortragstitels:
8th International Conference on Digital Audio Effects (DAFx 2005), Madrid, Spain
Sprache des Tagungstitel:
When using a mobile music player en-route, usually only little
attention can be paid to its handling. Nonetheless it is desirable
that all music stored in the device can be accessed quickly, and
that tracks played in a sequence should match up.
In this paper, we present an approach to satisfy these constraints:
a playlist containing all tracks stored in themusic player is
generated such that in average, consecutive pieces are maximally
similar. This is achieved by applying a Traveling Salesman algorithm
to the pieces, using timbral similarities as the distances. The
generated playlist is linear and circular, thus the whole collection
can easily be browsed with only one input wheel. When a chosen
track finishes playing, the player advances to the consecutive
tracks in the playlist, generally playing tracks similar to the chosen
track. This behavior could be a favorable alternative to the wellknown
shuffle function that most current devices – such as the iPod
shuffle, for example – have.
We evaluate the fitness of four different Traveling Salesman
algorithms for this purpose. Evaluated aspects were runtime, the
length of the resulting route, and the genre distribution entropy.
We implemented a Java applet to demonstrate the application
and its usability.