We present the design and evaluation of an in-
teractive tool for music exploration, with musi-
cal mood and genre inferred directly from tracks.
It uses probabilistic representations of multivari-
able predictions of subjective characteristics of
the music to give users subtle, nuanced visuali-
sations of the 2D map. These explicitly repre-
sent the uncertainty and overlap among features
and support music exploration and casual playlist
generation. A longitudinal trial in users’ homes
showed that probabilistic highlighting of subjec-
tive features led to more focused exploration in
mouse activity logs, and 6 of 8 users preferred
the probabilistic highlighting
