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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1860-4862 ader to understand the concepts better.Uses Matlab illustrat.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 basi

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Book 2014 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 (illustr

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Book 2014s 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..

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https://doi.org/10.1057/978-1-137-55408-6es of the vocal tract filter, cepstrual co-efficients, mel-frequency cepstral co-efficients (MFCC), line spectral co-efficients, and reflection co-efficients are discussed in this chapter. The preprocessing techniques such as dynamic time warping, endpoint detection, and pre-emphasis are also discussed in this chapter.

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1860-4862 deals with the basic pattern recognition techniques (illustrated with speech signals using Matlab) such as PCA, LDA, ICA, SVM, HMM, GMM, BPN, and KSOM..978-81-322-2897-4978-81-322-1677-3Series ISSN 1860-4862 Series E-ISSN 1860-4870

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Speech Production Model,lated speech recognition and the speaker recognition. It is used to compress the speech signal for storage like in Code exited linear prediction (CELP). It is useful for converting text into speech, known as speech synthesis. It is also used for continuous speech recognition. This chapter deals with the source-filter model of speech production.

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