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Titlebook: Digital Speech Processing Using Matlab; E. S. Gopi Book 2014 Springer India 2014 DSP Using Matlab.Digital Speech Processing.Hidden Markov

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發(fā)表于 2025-3-21 19:19:57 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Digital Speech Processing Using Matlab
編輯E. S. Gopi
視頻videohttp://file.papertrans.cn/280/279714/279714.mp4
概述Useful to beginners doing research in speech processing.Explains basic concepts of speech processing using Matlab illustrations.Helps the reader to understand the concepts better.Uses Matlab illustrat
叢書名稱Signals and Communication Technology
圖書封面Titlebook: Digital Speech Processing Using Matlab;  E. S. Gopi Book 2014 Springer India 2014 DSP Using Matlab.Digital Speech Processing.Hidden Markov
描述.Digital Speech Processing Using Matlab. deals with digital speech pattern recognition, speech production model, speech feature extraction, and speech compression. The book is written in a manner that is suitable for beginners pursuing basic research in digital speech processing. Matlab illustrations are provided for most topics to enable better understanding of concepts. This book also deals with the basic pattern recognition techniques (illustrated with speech signals using Matlab) such as PCA, LDA, ICA, SVM, HMM, GMM, BPN, and KSOM..
出版日期Book 2014
關(guān)鍵詞DSP Using Matlab; Digital Speech Processing; Hidden Markov Model; Speech Compression; Speech Pattern Rec
版次1
doihttps://doi.org/10.1007/978-81-322-1677-3
isbn_softcover978-81-322-2897-4
isbn_ebook978-81-322-1677-3Series ISSN 1860-4862 Series E-ISSN 1860-4870
issn_series 1860-4862
copyrightSpringer India 2014
The information of publication is updating

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發(fā)表于 2025-3-21 20:38:09 | 只看該作者
Speech Production Model,al speech signal thus obtained is sampled to obtain the discrete signals and are stored in the digital system for further processing. This is digital speech processing. The speech signal model is broadly classified as the source-filter model and the probabilistic model. Source-filter model assumes t
板凳
發(fā)表于 2025-3-22 01:44:57 | 只看該作者
Feature Extraction of the Speech Signal,is subjected to pattern recognition to formulate the classifier. The feature vector is extracted from each frame of the speech signal under test. In this chapter, various parameter extraction techniques such as linear predictive co-efficients as the filter co-efficients of the vocal tract model, pol
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發(fā)表于 2025-3-22 08:47:11 | 只看該作者
E. S. GopiUseful to beginners doing research in speech processing.Explains basic concepts of speech processing using Matlab illustrations.Helps the reader to understand the concepts better.Uses Matlab illustrat
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Ljiljana Brankovic,Helen Gigginsal speech signal thus obtained is sampled to obtain the discrete signals and are stored in the digital system for further processing. This is digital speech processing. The speech signal model is broadly classified as the source-filter model and the probabilistic model. Source-filter model assumes t
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