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The stationary bionic wavelet transf...

Mourad, Talbi.

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The stationary bionic wavelet transform and its applications for ECG and speech processing

Record Type:	Electronic resources : Monograph/item
Title/Author:	The stationary bionic wavelet transform and its applications for ECG and speech processing/ by Talbi Mourad.
Author:	Mourad, Talbi.
Published:	Cham :Springer International Publishing : : 2022.,
Description:	xiv, 84 p. :ill. (some col.), digital ;24 cm.
[NT 15003449]:	1. Speech enhancement based on stationary bionic wavelet transform and maximum a posterior estimator of magnitude-squared spectrum -- 2. ECG denoising based on 1-D double-density complex DWT and SBWT -- 3. Speech Enhancement based on SBWT and MMSE Estimate of Spectral Amplitude -- 4. Arabic Speech Recognition by Stationary Bionic Wavelet Transform and MFCC using a Multi-Layer Perceptron for Voice Control.
Contained By:	Springer Nature eBook
Subject:	Speech processing systems - Mathematics. -
Online resource:	https://doi.org/10.1007/978-3-030-93405-7
ISBN:	9783030934057

The stationary bionic wavelet transform and its applications for ECG and speech processing
Mourad, Talbi.

The stationary bionic wavelet transform and its applications for ECG and speech processing[electronic resource] /by Talbi Mourad. - Cham :Springer International Publishing :2022. - xiv, 84 p. :ill. (some col.), digital ;24 cm. - Signals and communication technology,1860-4870. - Signals and communication technology..

1. Speech enhancement based on stationary bionic wavelet transform and maximum a posterior estimator of magnitude-squared spectrum -- 2. ECG denoising based on 1-D double-density complex DWT and SBWT -- 3. Speech Enhancement based on SBWT and MMSE Estimate of Spectral Amplitude -- 4. Arabic Speech Recognition by Stationary Bionic Wavelet Transform and MFCC using a Multi-Layer Perceptron for Voice Control.

This book first details a proposed Stationary Bionic Wavelet Transform (SBWT) for use in speech processing. The author then details the proposed techniques based on SBWT. These techniques are relevant to speech enhancement, speech recognition, and ECG de-noising. The techniques are then evaluated by comparing them to a number of methods existing in literature. For evaluating the proposed techniques, results are applied to different speech and ECG signals and their performances are justified from the results obtained from using objective criterion such as SNR, SSNR, PSNR, PESQ, MAE, MSE and more. Describes and applies a proposed Stationary Bionic Wavelet Transform (SBWT) Discusses how speech enhancement, speech recognition, and ECG de-noising are aided by SBWTs Relevant to researchers, professionals, students, and academics in speech and ECG processing.

ISBN: 9783030934057

Standard No.: 10.1007/978-3-030-93405-7doiSubjects--Topical Terms:

3595539
Speech processing systems
--Mathematics.

LC Class. No.: TK7882.S65 / M68 2022

Dewey Class. No.: 621.3822

The stationary bionic wavelet transform and its applications for ECG and speech processing
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300 $a xiv, 84 p. : $b ill. (some col.), digital ; $c 24 cm.
490 1 $a Signals and communication technology, $x 1860-4870
505 0 $a 1. Speech enhancement based on stationary bionic wavelet transform and maximum a posterior estimator of magnitude-squared spectrum -- 2. ECG denoising based on 1-D double-density complex DWT and SBWT -- 3. Speech Enhancement based on SBWT and MMSE Estimate of Spectral Amplitude -- 4. Arabic Speech Recognition by Stationary Bionic Wavelet Transform and MFCC using a Multi-Layer Perceptron for Voice Control.
520 $a This book first details a proposed Stationary Bionic Wavelet Transform (SBWT) for use in speech processing. The author then details the proposed techniques based on SBWT. These techniques are relevant to speech enhancement, speech recognition, and ECG de-noising. The techniques are then evaluated by comparing them to a number of methods existing in literature. For evaluating the proposed techniques, results are applied to different speech and ECG signals and their performances are justified from the results obtained from using objective criterion such as SNR, SSNR, PSNR, PESQ, MAE, MSE and more. Describes and applies a proposed Stationary Bionic Wavelet Transform (SBWT) Discusses how speech enhancement, speech recognition, and ECG de-noising are aided by SBWTs Relevant to researchers, professionals, students, and academics in speech and ECG processing.
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