Advance Compression and Watermarking Technique for Speech Signals

Nonfiction, Science & Nature, Technology, Electronics, Reference & Language, Language Arts, Linguistics
Cover of the book Advance Compression and Watermarking Technique for Speech Signals by Komal Borisagar, Rohit Thanki, Surekha Borra, Springer International Publishing
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Author: Komal Borisagar, Rohit Thanki, Surekha Borra ISBN: 9783319690698
Publisher: Springer International Publishing Publication: November 3, 2017
Imprint: Springer Language: English
Author: Komal Borisagar, Rohit Thanki, Surekha Borra
ISBN: 9783319690698
Publisher: Springer International Publishing
Publication: November 3, 2017
Imprint: Springer
Language: English

This book introduces methods for copyright protection and compression for speech signals. The first method introduces copyright protection of speech signal using watermarking; the second introduces compression of the speech signal using Compressive Sensing (CS). Both methods are tested and analyzed. The speech watermarking method uses technology such as Finite Ridgelet Transform (FRT), Discrete Wavelet Transform (DWT) and Singular Value Decomposition (SVD). The performance of the method is evaluated and compared with existing watermarking methods. In the speech compression method, the standard Compressive Sensing (CS) process is used for compression of the speech signal. The performance of the proposed method is evaluated using various transform bases like Discrete Fourier Transform (DFT), Discrete Cosine Transform (DCT), Discrete Wavelet Transform (DWT), Singular Value Decomposition (SVD), and Fast Discrete Curvelet Transform (FDCuT).

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This book introduces methods for copyright protection and compression for speech signals. The first method introduces copyright protection of speech signal using watermarking; the second introduces compression of the speech signal using Compressive Sensing (CS). Both methods are tested and analyzed. The speech watermarking method uses technology such as Finite Ridgelet Transform (FRT), Discrete Wavelet Transform (DWT) and Singular Value Decomposition (SVD). The performance of the method is evaluated and compared with existing watermarking methods. In the speech compression method, the standard Compressive Sensing (CS) process is used for compression of the speech signal. The performance of the proposed method is evaluated using various transform bases like Discrete Fourier Transform (DFT), Discrete Cosine Transform (DCT), Discrete Wavelet Transform (DWT), Singular Value Decomposition (SVD), and Fast Discrete Curvelet Transform (FDCuT).

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