Recurrent neural-network-based physical model for the Chin and other plucked-string instruments

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5 Citations (Scopus)

Abstract

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.

Original languageEnglish
Pages (from-to)1045-1059
Number of pages15
JournalAES: Journal of the Audio Engineering Society
Volume48
Issue number11
Publication statusPublished - 2000 Nov 1

All Science Journal Classification (ASJC) codes

  • Engineering(all)
  • Music

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