Adaptive Temporal Modeling of Audio Features in the Context of Music Structure Segmentation

This paper describes a method for automatically adapting the length of the temporal modeling applied to audio features in the context of music structure segmentation. By detecting regions of homogeneous acoustical content and abrupt changes in the audio feature sequence, we show that we can consequently adapt temporal modeling to capture both fastand slowvarying structural information in the audio signal. Evaluation of the method shows that temporal modeling is consistently adapted to different musical contexts, allowing for robust music structure segmentation while gaining independence regarding parameter tuning.