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
Publication Date: November 1, 2000

Click to purchase paper as a non-member or you can login as an AES member to see more options.

No AES members have commented on this paper yet.

Subscribe to this discussion

To be notified of new comments on this paper you can subscribe to this RSS feed. Forum users should login to see additional options.

Start a discussion!

If you would like to start a discussion about this paper and are an AES member then you can login here:
Username:
Password:

If you are not yet an AES member and have something important to say about this paper then we urge you to join the AES today and make your voice heard. You can join online today by clicking here.