Advance Compression and Watermarking Technique for Speech Signals (SpringerBriefs in Speech Technology) - Softcover

Thanki, Rohit; Borisagar, Komal; Borra, Surekha

Softcover

ISBN 10: 331969068X ISBN 13: 9783319690681

Publisher: Springer, 2017

Synopsis

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).

About this title

About the Author

Rohit Thanki obtained his Ph.D. in Multibiometric System Security from C. U. Shah University, Wadhwan city, Gujarat, India in 2017. His area of research interest is Digital Watermarking, Biometrics System, Security, Compressive Sensing, Pattern Recognition and Image Processing. He has published 2 books, 3 book chapters and 23 research papers to his credit in refereed & indexed journals, and conference at international and national level. His international recognition includes his professional memberships & services in refereed organizations, programme committees and reviewer for journals published by IEEE, Elsevier, Taylor & Francis, Springer, IGI-Global etc.

Komal Borisagar is currently an Associate Professor in the Department of ECE, Atmiya Institute of Technology and Science, Rajkot, Gujarat, India. She earned her Doctorate in Speech Processing form JJTU, Rajasthan in 2012. Her area of research interest is Digital Watermarking, Medical Image Compression, Wireless Communication, Speech Processing, and Image Processing. She has published 1 book chapters and more than 40 research papers to her credit in refereed & indexed journals, and conferences at international and national levels.

Surekha Borra is currently a Professor in the Department of ECE, K. S. Institute of Technology, Bangalore, Karnataka, India. She earned her Doctorate in Image Processing from Jawaharlal Nehru Technological University, Hyderabad, India, in 2015.  Her research interests are in the areas of Image and Video Analytics, Machine Learning, Biometrics and Remote Sensing. She has published 4 book chapters and 22 research papers to her credit in refereed & indexed journals, and conferences at international and national levels. Her international recognition includes her professional memberships & services in refereed organizations, programme committees, editorial & review boards, wherein she has been a guest editor for 2journals and reviewer for journals published by IEEE, IET, Elsevier, Taylor & Francis, Springer, IGI-Global etc.,. She has received Woman Achiever's Award from The Institution of Engineers (India), for her prominent research and innovative contribution (s)., Woman Educator & Scholar Award for her contributions to teaching and scholarly activities, Young Woman Achiever Award for her contribution in Copyright Protection of Images.

From the Back Cover

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).

• Provides new technique for speech watermarking and speech compression;
  
• Presents a comprehensive review of speech watermarking techniques in spatial and transform domain;
  
• Describes a robust and secure watermarking technique for speech signals and addresses the issue of copyright protection of speech signals;
  
• Presents a comprehensive review of digital signal compression techniques using Compressive Sensing (CS);
  
• Describes application of Compressive Sensing (CS) for compression of speech signals and addresses the issue of compression of speech signals.

Edition details

• Publisher: Springer
• Publication date: 2017
• Language: English
• ISBN 10: 331969068X
• ISBN 13: 9783319690681
• Binding: Paperback
• Edition number: 1
• Number of pages: 87