A multi-channel recurrent network for synthesizing struck coupled-string musical instruments

Abstract

Struck string instruments, such as pianos, usually have groups of strings with each group terminated at a common bridge. Because of the strong coupling phenomenon, the produced tones exhibit highly complex amplitude modulation patterns. Therefore, it is difficult to determine synthesis model parameters such that the synthesized tones can match recorded tones. A multi-channel recurrent network is proposed based on three previous works: the coupled-string model, the commuted piano synthesis method and the IIR synthesis method. This work attempts to extract automatically the synthesis parameters by using a neural-network training algorithm without the knowledge of the physical properties of the instruments. Computer simulations show encouraging results.