DocumentCode
1299722
Title
Model-based synthesis of plucked string instruments by using a class of scattering recurrent networks
Author
Liang, Sheng-Fu ; Su, Alvin W Y ; Lin, Chin-Teng
Author_Institution
Dept. of Electr. & Control Eng., Nat. Chiao Tung Univ., Hsinchu, Taiwan
Volume
11
Issue
1
fYear
2000
fDate
1/1/2000 12:00:00 AM
Firstpage
171
Lastpage
185
Abstract
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 trained, it can be regarded as the virtual model for the measured string and used to generate tones which can be very close to those generated by its acoustic counterpart. The “virtual string” corresponding to the SRN can respond to different “plucks” just like a real string, which is impossible using traditional synthesis techniques such as frequency modulation and wavetable. The simulation of modeling a cello “A”-string demonstrates some encouraging results of the new music synthesis technique. Some aspects of modeling and synthesis procedures are also discussed
Keywords
electronic music; frequency modulation; learning (artificial intelligence); musical instruments; recurrent neural nets; acoustic strings; electronic music synthesis; measured vibration; model-based synthesis; physical modeling method; plucked string instruments; plucked-string tones; scattering recurrent networks; string dynamics; supervised learning; virtual model; Acoustic measurements; Acoustic scattering; Electronic music; Frequency modulation; Instruments; Network synthesis; Physics; Supervised learning; Training data; Vibration measurement;
fLanguage
English
Journal_Title
Neural Networks, IEEE Transactions on
Publisher
ieee
ISSN
1045-9227
Type
jour
DOI
10.1109/72.822519
Filename
822519
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