Synthesizing sound textures through wavelet tree learning

Shlomo Dubnov; Ziv Bar-Joseph; Ran El-Yaniv; Dani Lischinski; Michael Werman

doi:10.1109/MCG.2002.1016697

Synthesizing sound textures through wavelet tree learning

Shlomo Dubnov, Ziv Bar-Joseph, Ran El-Yaniv, Dani Lischinski, Michael Werman

Department of Communication Systems Engineering

Research output: Contribution to journal › Article › peer-review

61 Scopus citations

Abstract

Natural sounds are complex phenomena which contain a mixture of events localized in time and frequency. As such, a statistical learning algorithm for synthesizing random instances of sound textures from an existing natural sound example is presented. It describes sound textures as a set of repeating structural elements subject to some randomness in their time appearance and relative ordering but preserving certain essential temporal coherence and across-scale localization.

Original language	English
Pages (from-to)	38-48
Number of pages	11
Journal	IEEE Computer Graphics and Applications
Volume	22
Issue number	4
DOIs	https://doi.org/10.1109/MCG.2002.1016697
State	Published - 1 Jul 2002

ASJC Scopus subject areas

Software
Computer Graphics and Computer-Aided Design

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10.1109/MCG.2002.1016697

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title = "Synthesizing sound textures through wavelet tree learning",

abstract = "Natural sounds are complex phenomena which contain a mixture of events localized in time and frequency. As such, a statistical learning algorithm for synthesizing random instances of sound textures from an existing natural sound example is presented. It describes sound textures as a set of repeating structural elements subject to some randomness in their time appearance and relative ordering but preserving certain essential temporal coherence and across-scale localization.",

author = "Shlomo Dubnov and Ziv Bar-Joseph and Ran El-Yaniv and Dani Lischinski and Michael Werman",

note = "Funding Information: We presented a preliminary version of this article at the International Computer Music Conference (ICMC 99). This research was supported in part by the Israel Science Foundation founded by the Israel Academy of Sciences and Humanities. Ran El-Yaniv is a Marcella S. Geltman Memorial Academic Lecturer.",

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AU - Dubnov, Shlomo

AU - Bar-Joseph, Ziv

AU - El-Yaniv, Ran

AU - Lischinski, Dani

AU - Werman, Michael

N1 - Funding Information: We presented a preliminary version of this article at the International Computer Music Conference (ICMC 99). This research was supported in part by the Israel Science Foundation founded by the Israel Academy of Sciences and Humanities. Ran El-Yaniv is a Marcella S. Geltman Memorial Academic Lecturer.

PY - 2002/7/1

Y1 - 2002/7/1

N2 - Natural sounds are complex phenomena which contain a mixture of events localized in time and frequency. As such, a statistical learning algorithm for synthesizing random instances of sound textures from an existing natural sound example is presented. It describes sound textures as a set of repeating structural elements subject to some randomness in their time appearance and relative ordering but preserving certain essential temporal coherence and across-scale localization.

AB - Natural sounds are complex phenomena which contain a mixture of events localized in time and frequency. As such, a statistical learning algorithm for synthesizing random instances of sound textures from an existing natural sound example is presented. It describes sound textures as a set of repeating structural elements subject to some randomness in their time appearance and relative ordering but preserving certain essential temporal coherence and across-scale localization.

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DO - 10.1109/MCG.2002.1016697

M3 - Article

AN - SCOPUS:0036647395

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SP - 38

EP - 48

JO - IEEE Computer Graphics and Applications

JF - IEEE Computer Graphics and Applications

IS - 4

ER -

Synthesizing sound textures through wavelet tree learning

Abstract

ASJC Scopus subject areas

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