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Titlebook: Speech Processing and Soft Computing; Sid-Ahmed Selouani Book 2011 Springer Science+Business Media, LLC 2011 Artificial neural networks.Ge

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发表于 2025-3-21 19:23:31 | 显示全部楼层 |阅读模式
书目名称Speech Processing and Soft Computing
编辑Sid-Ahmed Selouani
视频video
概述Focuses on the missing link between speech technology and soft computing.Contains coverage of the innovative approaches in speech technology.Gives new insights in speech recognition/enhancement obtain
丛书名称SpringerBriefs in Electrical and Computer Engineering
图书封面Titlebook: Speech Processing and Soft Computing;  Sid-Ahmed Selouani Book 2011 Springer Science+Business Media, LLC 2011 Artificial neural networks.Ge
描述.Speech Processing and Soft Computing. includes coverage of synergy between speech technology and bio-inspired soft computing methods. Through practical cases, the author explores, dissects and examines how soft computing may complement conventional techniques in speech enhancement and speech recognition in order to provide robust systems. The material is especially useful to graduate students and experienced researchers who are interested in expanding their horizons and investigating new research directions through review of the theoretical and practical settings of soft computing methods in very recent speech applications.
出版日期Book 2011
关键词Artificial neural networks; Genetic algorithms; Human to computer interaction; Signal processsing; Soft
版次1
doihttps://doi.org/10.1007/978-1-4419-9685-5
isbn_softcover978-1-4419-9684-8
isbn_ebook978-1-4419-9685-5Series ISSN 2191-8112 Series E-ISSN 2191-8120
issn_series 2191-8112
copyrightSpringer Science+Business Media, LLC 2011
The information of publication is updating

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Book 2011al cases, the author explores, dissects and examines how soft computing may complement conventional techniques in speech enhancement and speech recognition in order to provide robust systems. The material is especially useful to graduate students and experienced researchers who are interested in exp
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Variance of the Reconstruction Error Techniquell remain. The purpose of this chapter is to present a signal subspace decomposition method using a Variance of Reconstruction Error (VRE) criterion to optimally select principal components. A benchmarking of various methods for selecting the number of PCs in a speech enhancement application is performed using data from the NOIZEUS database.
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