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A Multichannel Recurrent Network Analysis/Synthesis Model for Coupled-String Instruments.

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Title: A Multichannel Recurrent Network Analysis/Synthesis Model for Coupled-String Instruments.
Authors: Wei-Chen Chang1, Su, Alvin W. Y.1,2 alvinsu@mail.ncku.edu.tw
Source: IEEE Transactions on Audio, Speech & Language Processing. Nov2006, Vol. 14 Issue 6, p2233-2241. 9p. 5 Diagrams, 1 Chart, 8 Graphs.
Subjects: Algorithms, Piano, Keyboard instruments, Computer simulation, Simulation methods & models
Abstract: Struck-string instruments such as pianos usually have groups of strings that terminate at some common bridges. Because of the strong coupling phenomenon, the produced tones can exhibit highly complex modulation patterns, and synthesizing such complex tones turns out to be quite complicated. It is also difficult to determine the synthesis model parameters such that the synthesized tones can match the recorded tones. This paper proposes a multichannel recurrent network based on three previous works: the coupled-string model, the commuted piano synthesis method, and the infinite impulse response (IIR) synthesis method. This work attempts to automatically extract the synthesis parameters by using a neural-network training algorithm without the knowledge of the instruments' physical properties. Encouraging results are shown in the computer simulations. [ABSTRACT FROM AUTHOR]
Copyright of IEEE Transactions on Audio, Speech & Language Processing is the property of IEEE and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: A Multichannel Recurrent Network Analysis/Synthesis Model for Coupled-String Instruments.
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  Data: <searchLink fieldCode="AR" term="%22Wei-Chen+Chang%22">Wei-Chen Chang</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Su%2C+Alvin+W%2E+Y%2E%22">Su, Alvin W. Y.</searchLink><relatesTo>1,2</relatesTo><i> alvinsu@mail.ncku.edu.tw</i>
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  Data: <searchLink fieldCode="DE" term="%22Algorithms%22">Algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Piano%22">Piano</searchLink><br /><searchLink fieldCode="DE" term="%22Keyboard+instruments%22">Keyboard instruments</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+simulation%22">Computer simulation</searchLink><br /><searchLink fieldCode="DE" term="%22Simulation+methods+%26+models%22">Simulation methods & models</searchLink>
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  Data: Struck-string instruments such as pianos usually have groups of strings that terminate at some common bridges. Because of the strong coupling phenomenon, the produced tones can exhibit highly complex modulation patterns, and synthesizing such complex tones turns out to be quite complicated. It is also difficult to determine the synthesis model parameters such that the synthesized tones can match the recorded tones. This paper proposes a multichannel recurrent network based on three previous works: the coupled-string model, the commuted piano synthesis method, and the infinite impulse response (IIR) synthesis method. This work attempts to automatically extract the synthesis parameters by using a neural-network training algorithm without the knowledge of the instruments' physical properties. Encouraging results are shown in the computer simulations. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of IEEE Transactions on Audio, Speech & Language Processing is the property of IEEE and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1109/TASL.2006.872610
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      – SubjectFull: Keyboard instruments
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      – SubjectFull: Computer simulation
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