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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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发表于 2025-3-21 19:19:57 | 显示全部楼层 |阅读模式
书目名称Digital Speech Processing Using Matlab
编辑E. S. Gopi
视频video
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
丛书名称Signals and Communication Technology
图书封面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
关键词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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发表于 2025-3-21 20:38:09 | 显示全部楼层
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
发表于 2025-3-22 01:44:57 | 显示全部楼层
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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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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