This thesis aims at developing techniques which support users in accessing and discovering
music. The main part consists of two chapters. Chapter 2 gives an introduction to …

We present a novel approach for analysing and classifying lyrics, experimenting both with
ngram models and more sophisticated features that model different dimensions of a song …

How individuals perceive music is influenced by many different factors. The audible part of a
piece of music, its sound, does for sure contribute, but is only one aspect to be taken into …

We present a freely available benchmark dataset for audio classification and clustering. This
dataset consists of 10 seconds samples of 1886 songs obtained from the Garageband site …

The ever-growing amount of available music induces an increasing demand for Music
Information Retrieval (MIR) applications such as music recommendation applications or …

Large music collections require new ways to let users interact with their music. The concept
of finding” similar 'songs, albums, or artists provides handles to users for easy navigation …

In many areas multimedia technology has made its way into mainstream. In the case of
digital audio this is manifested in numerous online music stores having turned into profitable …

MusicSun is a graphical user interface to discover artists. Artists are recommended based on
one or more artists selected by the user. The recommendations are computed by combining …

The majority of systems extracting high-level music descriptions from audio signals rely on a
common, implicit model of the global sound or polyphonic timbre of a musical signal. This …

As digital music collections grow, so does the need to organizing them automatically. In this
paper we present an approach to hierarchically organize music collections at the artist level …