Representing the evolving temporal envelope of musical instruments sounds using Computer Vision methods

This paper proposes application of shape retrieval method developed and used in the domain of Computer Vision to describe and to match the long-term temporal envelope of musical instruments sounds that are to be compared. To effectively describe each envelope, we employ the skeleton descriptor, namely Audio Skeleton, to integrate both geometrical and topological envelope features. Based on skeletons, the audio envelope matching can be substituted by searching for the correspondences of skeleton endpoints. Finally, the similarity of audio envelopes is calculated based on their correlated skeleton matching. Our main contributions include (i) the introduction of a novel audio envelope descriptor with skeleton and (ii) the efficient and fast audio skeleton pruning and matching algorithms. Our method is validated through the skeleton matching and audio retrieval experiments on AMATI violin sound dataset.