Scalable Music: Automatic Music Retargeting and Synthesis

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In this paper we propose a method for dynamic rescaling of music, inspired by recent works on image retargeting, video reshuffling and character animation in the computer graphics community. Given the desired target length of a piece of music and optional additional constraints such as position and importance of certain parts, we build on concepts from seam carving, video textures and motion graphs and extend them to allow for a global optimization of jumps in an audio signal. Based on an automatic feature extraction and spectral clustering for segmentation, we employ length-constrained least-costly path search via dynamic programming to synthesize a novel piece of music that best fulfills all desired constraints, with imperceptible transitions between reshuffled parts. We show various applications of music retargeting such as part removal, decreasing or increasing music duration, and in particular consistent joint video and audio editing.
Publisher
WILEY-BLACKWELL
Issue Date
2013-05
Language
English
Article Type
Article
Citation

COMPUTER GRAPHICS FORUM, v.32, no.2, pp.345 - 354

ISSN
0167-7055
DOI
10.1111/cgf.12054
URI
http://hdl.handle.net/10203/225182
Appears in Collection
GCT-Journal Papers(저널논문)
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