Multiple hypotheses at multiple scales for audio novelty computation within music

Novelty-based segmentation of audio signals has proven good performances for the estimation of boundaries of structural sections within music pieces. However, boundaries are detected only if structural sections satisfy the condition of sufficient acoustic inner-homogeneity. While this constraint is very restrictive and not representative of all musical contents, we propose in this paper to extend the detection of acoustic novelty to transitions between homogeneous and non-homogeneous sections and vice versa. Moreover, the length of the considered sections for the boundary detection is crucial, we also introduce a multi-scale novelty approach that allows to capture boundaries between sections of different temporal scales in a same segmentation. Evaluation of the combination of these two methods proves convincing results for temporal segmentation of music pieces. Embedding the algorithm in a music structure segmentation system, we show that performances can be consistently improved for this task.