In a time of increased interest in security assurance, all topics related to watermarking are important. While the book’s focus is securing speech, a technologically related problem of compression is also covered. While we are mostly used to image watermarking, security applications for a somewhat different kind of signal are especially welcome.

This is not a typical textbook. While some general material is given at the beginning, the book resembles an extended paper focused on a specialized application. On the other hand, this is not unusual for a “Springer Briefs in Electrical and Computer Engineering” book.

Chapters 1 and 2 present the introductory data necessary to understand the authors’ original approaches in chapters 3 and 4. (Chapter 5 is only a short summary of the whole book.) The first part sketches the following concepts: basic properties of the speech signals and fundamentals of digital watermarking (such as various desired properties and main applications). Compressive sensing is also described, since the authors use it in their approach in chapter 4. Furthermore, chapter 2 characterizes various digital signal transforms (discrete Fourier transform, discrete cosine transform, discrete wavelet transform, singular value decomposition, fast discrete curvelet transform, and finite ridgelet transform). The Arnold scrambling transform, which the authors apply in the book’s main part (chapter 3), is then shortly discussed. Similarly, compressive sensing reconstruction algorithms are covered.

In the part devoted to the original solution, Thanki et al. present their own concept of speech watermarking based on the finite ridgelet transform, the discrete wavelet transform, singular value decomposition, as well as the forward Arnold scrambling transform (chapter 3). They cover the algorithms for watermark embedding and extraction, as well as provide illustrative experimental examples. They also elaborate on additional aspects, such as embedding capacity and comparisons with other methods. The next chapter presents a somewhat related (a similar set of transforms is applied) concept of compression for speech. It is based on compressive sensing.

This short book will be of interest to specialists in speech processing. It is likely too difficult for laypeople, who--if they are interested in watermarking--should first start with a textbook dealing with much more basic material.