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
Link To Document :
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