Title :
Morphing dynamical sound models
Author_Institution :
Tech. Univ. Berlin, Germany
fDate :
31 Aug-2 Sep 1998
Abstract :
We investigate a new approach to sound morphing that is strictly in the time domain. It is based upon a method of modeling and synthesizing natural sounds with neural networks that has been introduced previously and is called dynamic or attractor modeling. By means of basic synthetic signals we investigate the fundamental properties of the proposed morphing scheme. Using two real world sound signals obtained from a saxophone we demonstrate the potential of the method when applied to complex natural sounds
Keywords :
discrete time systems; neural nets; nonlinear dynamical systems; signal synthesis; time series; attractor modeling; dynamic modeling; dynamical sound models; natural sounds; neural networks; saxophone; sound morphing; synthetic signals; time domain; Algorithm design and analysis; Chaos; Instruments; Network synthesis; Neural networks; Signal analysis; Signal generators; Signal synthesis; Stability; State-space methods;
Conference_Titel :
Neural Networks for Signal Processing VIII, 1998. Proceedings of the 1998 IEEE Signal Processing Society Workshop
Conference_Location :
Cambridge
Print_ISBN :
0-7803-5060-X
DOI :
10.1109/NNSP.1998.710671
