Abstract
In this paper different digital audio watermarking techniques have been proposed. Currently, more attention is given to combination of Discrete Wavelet Transform (DWT) and Singular Value Decomposition (SVD) techniques for watermarking purpose. Available DWT–SVD audio watermarking techniques cannot be applied to speech signals efficiently. However, Linear Predictive Analysis (LPA) technique can model digital speech signals (20–30 ms) in more flexible and efficient ways than DWT. In this paper, a novel digital speech watermarking technique is proposed by applying both LPA and SVD. Quantization Index Modulation (QIM) is further applied to embed the watermark bits. The experimental results show that not only time and memory were reduced significantly as compared to different DWT–SVD audio watermarking techniques, but also the proposed technique was more robust and imperceptible for speech watermarking than other DWT–SVD audio watermarking techniques.












Similar content being viewed by others
References
Katzenbeisser S, Petitcolas F (2000) Information hiding techniques for steganography and digital watermarking. Artech house, Massachusetts
Nematollahi MA et al (2015) Semi-fragile digital speech watermarking for online speaker recognition. EURASIP J Audio Speech Music Process 2015(1):1–15
Hofbauer K, Kubin G, Kleijn WB (2009) Speech watermarking for analog flat-fading bandpass channels. Audio Speech Lang Process IEEE Trans 17(8):1624–1637
Djebbar F et al (2012) Comparative study of digital audio steganography techniques. EURASIP J Audio Speech Music Process 2012(1):1–16
Nematollahi MA, Al-Haddad S (2013) An overview of digital speech watermarking. Int J Speech Technol 16(4):471–488
Dhar PK, Shimamura T (2013) A DWT–DCT–based audio watermarking method using singular value decomposition and quantization. J Signal Process 17(3):69–79
Lei BY, Soon Y, Li Z (2011) Blind and robust audio watermarking scheme based on SVD–DCT. Signal Process 91(8):1973–1984
Özer H, Sankur B, Memon N (2005) An SVD-based audio watermarking technique. In: Proceedings of the 7th workshop on multimedia and security. ACM
Wang J, Healy R, Timoney J (2011) A robust audio watermarking scheme based on reduced singular value decomposition and distortion removal. Signal Process 91(8):1693–1708
Al-Haj A, Mohammad AA, Bata L (2011) DWT-based audio watermarking. Int Arab J Inf Technol 8(3):326–333
Bhat V, Sengupta I, Das A (2011) An audio watermarking scheme using singular value decomposition and dither-modulation quantization. Multimed Tools Appl 52(2–3):369–383
Bhat V, Sengupta I, Das A (2011) A new audio watermarking scheme based on singular value decomposition and quantization. Circuits Syst Signal Process 30(5):915–927
Nematollahi MA, Al-Haddad S, Zarafshan F (2015) Blind digital speech watermarking based on Eigen-value quantization in DWT. J King Saud Univ Comput Inf Sci 27(1):58–67
Al-Yaman MS, Al-Taee MA, Alshammas HA (2012) Audio-watermarking based ownership verification system using enhanced DWT–SVD technique. In: Systems, Signals and Devices (SSD), 9th International Multi-Conference on 2012. IEEE
Lei B et al (2012) A robust audio watermarking scheme based on lifting wavelet transform and singular value decomposition. Signal Process 92(9):1985–2001
Mishra J, Patil MV, Chitode JS (2013) An effective audio watermarking using DWT–SVD. Int J Comput Appl 70(8):6–11
Verma A et al (2012) An efficient audio watermarking scheme based on SVD in wavelet domain and Chaotic Mapping. In: Engineering (NUiCONE), Nirma University International Conference on 2012. IEEE
Rabiner LR, Schafer RW (1978) Digital processing of speech signals. Prentice Hall, New Jersey
Al-Shoshan AI (2006) Speech and music classification and separation: a review. J King Saud Univ 19:95–133
Flanagan JL (2013) Speech analysis synthesis and perception. vol 3. Springer Science & Business Media
Nematollahi MA, Al-Haddad S (2015) Distant speaker recognition: an overview. Int J Hum Robot: 1550032
Vallabha GK, Tuller B (2002) Systematic errors in the formant analysis of steady-state vowels. Speech Commun 38(1):141–160
Zheng N (2006) Speaker recognition using complementary information from vocal source and vocal tract. The Chinese University of Hong Kong, People’s Republic of China
Nematollahi MA et al (2016) Speaker frame selection for digital speech watermarking. Natl Acad Sci Lett 39:1–5
Biglieri E, Yao K (1989) Some properties of singular value decomposition and their applications to digital signal processing. Signal Process 18(3):277–289
Al-Haj A, Mohammad A (2010) Digital audio watermarking based on the discrete wavelets transform and singular value decomposition. Eur J Sci Res 39(1):6–21
Wei-zhen J (2010) Notice of Retraction Fragile audio watermarking algorithm based on SVD and DWT. In: Intelligent Computing and Integrated Systems (ICISS), International Conference on 2010. IEEE
Bhat V, Sengupta I, Das A (2010) An adaptive audio watermarking based on the singular value decomposition in the wavelet domain. Digit Signal Process 20(6):1547–1558
Orović I, Stanković S (2010) Time-frequency-based speech regions characterization and eigenvalue decomposition applied to speech watermarking. EURASIP J Adv Signal Process 2010:4
Ebu, S., Sound Quality Assessment Material. 2006
Waters G (1988) Sound quality assessment material—recordings for subjective tests: user’s handbook for the ebu–sqam compact disk. European Broadcasting Union (EBU), Tech. Rep
Hofbauer K, Petrik S, Hering H (2008) The ATCOSIM corpus of non-prompted clean air traffic control speech. In: LREC
Johnson DH (2006) Signal-to-noise ratio. Scholarpedia 1(12):2088
Servan-Schreiber D (1990) Signal-to-noise ratio, and behavior. Science 24:9
Picovici D, Mahdi A (2001) Towards non-intrusive speech quality assessment for modern telecommunications. In: First Joint IEI/IEE Symposium of Telecom Systems Research. Citeseer
Verdu S, Han TS (1994) A general formula for channel capacity. Inf Theory IEEE Trans 40(4):1147–1157
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Nematollahi, M.A., Vorakulpipat, C., Gamboa-Rosales, H. et al. Digital Speech Watermarking Based on Linear Predictive Analysis and Singular Value Decomposition. Proc. Natl. Acad. Sci., India, Sect. A Phys. Sci. 87, 433–446 (2017). https://doi.org/10.1007/s40010-017-0371-8
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s40010-017-0371-8