Estimating double thumbnails for music recordings

Audio thumbnailing, which aims at finding the most representative audio segment of a music recording, is an important task in music information retrieval. In general, the notion of a thumbnail is not well-defined and several musical parts may be good thumbnail candidates. For example, for popular music, both a verse and a refrain section may serve as suitable thumbnail candidates. Instead of considering only one thumbnail, we consider in this paper the problem of finding the two most representative segments that correspond to different musical parts. We denote these two segments as double thumbnails. As our main technical contributions, we propose two approaches for computing double thumbnails, both extending a previously introduced repetition-based thumbnailing procedure. In the first approach, which is straightforward, we simply apply the original thumbnailing procedure two times in an iterative fashion. In the second approach, we introduce a novel method for jointly estimating the two thumbnails within one optimization procedure. Finally, we report on experimental results demonstrating the performances of the two double thumbnailing procedures and indicate directions towards full music structure analysis.