Scalability in Content-Based Navigation of Sound Databases
Résumé
The article presents methods for sound search in large effects or instrument sound databases by interactive content-based navigation in a space of descriptors and categories, based on the principle of real-time corpus-based concatenative synthesis. We focus on three algorithms: fast similarity-based search by a kD-Tree in the high-dimensional descriptor space, a mass--spring model with added repulsion for layout, and efficient dimensionality reduction for visualisation by hybrid multi-dimensional scaling based on these. Special attention is given to scalability to very large databases by performance evaluations and measurements. The algorithms are implemented and tested as C-libraries and Max/MSP externals within a prototype sound exploration application.
Domaines
Son [cs.SD] Interface homme-machine [cs.HC] Musique, musicologie et arts de la scène Informatique [cs] Traitement du signal et de l'image [eess.SP] Apprentissage [cs.LG] Intelligence artificielle [cs.AI] Ingénierie assistée par ordinateur Multimédia [cs.MM] Vision par ordinateur et reconnaissance de formes [cs.CV] Autre [cs.OH] Traitement du signal et de l'image [eess.SP]
Origine : Fichiers produits par l'(les) auteur(s)
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