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Recurrent Neural-Network-Based Physical Model for the Chin and Other Plucked-String Instruments

A new physical model with neural networks is presented. The structure of the network is designed for the analysis of plucked-string instruments, and this network is also used as the corresponding synthesis engine. The proposed approach also provides a general and automatic way of determining suitable synthesis parameters by using a supervised neural network training algorithm with recorded sounds of a specific played instrument as the training vector. This is a general method and can be used for any plucked-string instrument. A traditional Chinese plucked-string instrument, called the Chin, is used as the target instrument to demonstrate this new synthesis method.

Authors: Liang, Sheng-Fu; Su, Alvin W. Y.
Affiliations: Department of Electrical and Control Engineering, National Chiao-Tung University, Hsin-Chu, Taiwan ; Department of CSIE, National Cheng-Kung University, Tainan, Taiwan(See document for exact affiliation information.)
JAES Volume 48 Issue 11 pp. 1045-1059; November 2000 Import into BibTeX

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