Music thumbnailing (or music summarization) aims at finding the most representative part of a song, which can be used for web browsing, web searching and music recommendation. Three strategies are proposed in this paper for automatically generating the thumbnails of music. All the strategies are based on the results of music structural analysis, which identifies the recurrent structure of musical signals. Instead of being evaluated subjectively, the generated thumbnails are evaluated by several criteria, mainly based on previous human experiments on music thumbnailing and the properties of thumbnails used for commercial web sites. Additionally, the performance of the structural analysis is demonstrated visually using figures for qualitative evaluation, and by three novel structural similarity metrics for quantitative evaluation. The preliminary results obtained using a corpus of Beatles' songs demonstrate the promise of our method and suggest that different thumbnailing strategies might be proper for different applications.

Structured audio representations are semantic and symbolic descriptions that are useful for ultralow-bit-rate transmission, flexible synthesis, and perceptually based manipulation and retrieval of sound. We present an overview of techniques for transmitting and synthesizing sound represented in structured format, and for creating structured representations from audio waveforms. We discuss applications for structured audio in virtual environments, music synthesis, gaming, content-based retrieval, interactive broadcast, and other multimedia contexts.