This paper describes a novel way to combine a well-proven method of structural segmentation through novelty detection with a recently introduced method based on harmonic analysis. The former system works by looking for peaks in novelty curves derived from self-similarity matrices. The latter relies on the detection of key changes and on the differences in prior probability of chord transitions ...

This paper considers the application of a recently proposed L2 optimal nonparametric Reduced Set Density Estimator to novelty detection and binary classification and provides empirical comparisons with other forms of density estimation as well as Support Vector Machines.

Application of a neural network approach to data exploration and the generation of a model of system normality is described for use in novelty detection of vibration characteristics of a modern jet engine. The analysis of the shape of engine vibration signatures is shown to improve upon existing methods of engine vibration testing, in which engine vibrations are conventionally compared with a f...

We present a semi-supervised online method for novelty detection and evaluate its performance for radio astronomy time series data. Our approach uses adaptive eigenbases to combine 1) prior knowledge about uninteresting signals with 2) online estimation of the current data properties to enable highly sensitive and precise detection of novel signals. We apply the method to the problem of detecti...

The task of novelty detection with the objective of detecting changes regarding musical properties such as harmony, dynamics, timbre, or tempo is of fundamental importance when analyzing structural properties of music recordings. But for a specific audio version of a given piece of music, the novelty detection result may also crucially depend on the individual performance style of the musician....