Predictability of music descriptor time series and its application to cover song detection

Intuitively, music has both predictable and unpredictable components. In this work we assess this qualitative statement in a quantitative way using common time series models fitted to state-of-the-art music descriptors. These descriptors cover different musical facets and are extracted from a large collection of real audio recordings comprising a variety of musical genres. Our findings show that music descriptor time series exhibit a certain predictability not only for short time intervals, but also for mid-term and relatively long intervals. This fact is observed independently of the descriptor, musical facet and time series model we consider. Moreover, we show that our findings are not only of theoretical relevance but can also have practical impact. To this end we demonstrate that music predictability at relatively long time intervals can be exploited in a real-world application, namely the automatic identification of cover songs (i.e. different renditions or versions of the same musical piece). Importantly, this prediction strategy yields a parameter-free approach for cover song identification that is substantially faster, allows for reduced computational storage and still maintains highly competitive accuracies when compared to state-of-the-art systems.

Rearranging Phrasal Verbs

This paper starts from the fact that everyone who has studied English as a second languagehas noticed that the study of phrasal verbs poses a challenge for both teachers andstudents. Students are offered a list of phrasal verbs without any other explanation; theyjust have to learn them by heart. Those lists differ from one another due to the fact thateach author/teacher chooses the phrasal verbs that they consider the most common. Sincethis approach to phrasal verbs is not the most effective, it is going to be the center of thisstudy. After describing what a phrasal verb is –a compound verb formed by a main verband a particle–, although the particle placement will also be treated, the work will befocused on analyzing the particle in terms of meaning. Moreover, a comparison among itstreatment in different dictionaries will be carried out, and, since the particle is the keycomponent, we aim to reorganize the lists provided to students according to the particle inorder to make its study easier.

Die Präsenz des steirischen Dialekts im Internet

Die vorliegende Arbeit befasst sich mit der Präsenz deutscher Dialekte im Internet, wobei der Schwerpunkt auf dem österreichischen Dialekt Steirisch liegt. Es wird untersucht, in welchem Maße dieser Dialekt im Rahmen der Kommunikation via Internet verwendet wird