Conference paper Open Access

Interfacing Sounds: Hierarchical Audio-Content Morphologies for Creative Re-purposing in earGram 2.0

Bernardes, Gilberto

Editor(s)
Michon, Romain; Schroeder, Franziska

Audio content-based processing has become a pervasive methodology for techno-fluent musicians. System architectures typically create thumbnail audio descriptions, based on signal processing methods, to visualize, retrieve and transform musical audio efficiently. Towards enhanced usability of these descriptor-based frameworks for the music community, the paper advances a minimal content-based audio description scheme, rooted on primary musical notation attributes at the threefold sound object, meso and macro hierarchies. Multiple perceptually-guided viewpoints from rhythmic, harmonic, timbral and dynamic attributes define a discrete and finite alphabet with minimal formal and subjective assumptions using unsupervised and user-guided methods. The Factor Oracle automaton is then adopted to model and visualize temporal morphology. The generative musical applications enabled by the descriptor-based framework at multiple structural hierarchies are discussed.
Files (18.1 MB)
Name Size
nime2020_paper103.mp4
md5:66acb2983531bf680033389251e720eb
17.2 MB Download
nime2020_paper103.pdf
md5:71c349fec525aac18ff1f115c5ac7353
868.6 kB Download
nime2020_paper103.srt
md5:1d304f068d1e41ec835868559cdfcb10
10.8 kB Download
67
28
views
downloads
All versions This version
Views 6767
Downloads 2828
Data volume 40.7 MB40.7 MB
Unique views 4848
Unique downloads 2525

Share

Cite as