Multirate Extensions for Model-Based Synthesis of Plucked String Instruments

Nonlinear Modeling and Synthesis of the Kantele - a Traditional Finnish String Instrument

We apply a recently developed nonlinear string synthesis algorithm to modeling and synthesis of the kantele, which is a plucked string instrument used in traditional Finnish music for the past few thousand years. The new model combines formerly proposed linear plucked-string models with recent nonlinear extensions. As a result, a dual-polarization nonlinear model is obtained where the differenc...

Physical Modeling of Plucked String Instruments with Application to Real-Time Sound Synthesis*

An efficient approach for real-time synthesis of plucked string instruments using physical modeling and DSP techniques is presented. Results of model-based resynthesis are illustrated to demonstrate that high-quality synthetic sounds of several string instruments can be generated using the proposed modeling principles. Real-time implementation using a signal processor is described, and several ...

Aspects in analysis and model-based sound synthesis of plucked string instruments

A class of physical modeling recurrent networks for analysis/synthesis of plucked string instruments

A new approach is proposed that closely synthesizes tones of plucked string instruments by using a class of physical modeling recurrent networks. The strategies employed consist of a fast training algorithm and a multistage training procedure that are able to obtain the synthesis parameters for a specific instrument automatically. The training vector can be recorded tones of most target plucked...

Model-based synthesis of plucked string instruments by using a class of scattering recurrent networks

A physical modeling method for electronic music synthesis of plucked-string tones by using recurrent networks is proposed. A scattering recurrent network (SRN) which is used to analyze string dynamics is built based on the physics of acoustic strings. The measured vibration of a plucked string is employed as the training data for the supervised learning of the SRN. After the network is well tra...