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Book cover Advance Compression and Watermarking Technique for Speech Signals

Part of the book series: SpringerBriefs in Electrical and Computer Engineering ((BRIEFSSPEECHTECH))

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Abstract

This chapter presents the basic background of the speech signal and its characteristics. A basic overview of the watermarking technique and compressive sensing theory for the speech signal is also given in this chapter. Finally, the motivation for the presented research work is described.

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Bibliography

  • Baraniuk R (2007) Compressive sensing. IEEE Signal Process Mag 24:118–124

    Article  Google Scholar 

  • Bender W, Gruhl D, Morimoto N, Lu A (1996) Techniques for data hiding. IBM Syst J 35(3&4):313–336

    Article  Google Scholar 

  • Borra S, Swamy G (2013) Sensitive digital image watermarking for copyright protection. Int J Netw Secur 15(2):95–103

    Google Scholar 

  • Candes E (2006) Compressive sampling. In: Proceedings of the International Congress of Mathematicians, pp 1–20.

    Google Scholar 

  • Cox I, Kilian J, Shamoon T, Leighton F (1997) Secure spread spectrum watermarking for multimedia. IEEE Trans Image Process 6(12):1673–1687

    Article  Google Scholar 

  • Cox I, Miller M, Bloom J (2001) Digital watermarking. The Morgan Kaufmann Publishers, San Francisco

    Google Scholar 

  • Dai W, Milenkovic O (2009) Subspace pursuit for compressive sensing signal reconstruction. IEEE Trans Inf Theory 55(5):2230–2249

    Article  MATH  MathSciNet  Google Scholar 

  • Donoho D (2006) Compressed sensing. IEEE Trans Inf Theory 52(4):1289–1306

    Article  MATH  MathSciNet  Google Scholar 

  • Duarte M, Eldar Y (2011) Structured compressed sensing: from theory to applications. IEEE Trans Signal Process 59(9):4053–4085

    Article  MathSciNet  Google Scholar 

  • Gilbert A, Strauss M, Tropp J, Vershynin R (2007) One sketch for all: fast algorithms for compressed sensing. In: 39th ACM Symposium on Theory of Computing (STOC), ACM, New York, pp 237–246

    Google Scholar 

  • Hartung F, Kutter M (1999) Multimedia watermarking techniques. Proc IEEE 87(7):1085–1103

    Article  Google Scholar 

  • Homayoun A, Parsi K, Bouchard M (2009) Improved noise power spectrum density estimation for binaural hearing aids operating in a diffuse noise field environment. IEEE Trans Audio Speech Lang Process 17(4):521–533

    Article  Google Scholar 

  • Kim K, Ro Y (2004) Enhancement methods of image quality in screen mark attack. In: Kalker T et al (eds) IWDW 2003, LNCS 2939. Springer, Berlin, pp 474–482

    Google Scholar 

  • Langelaar G, Setyawan I, Lagendijk R (2000) Watermarking of digital image and video data—a state of art review. IEEE Signal Process Mag 17:20–46

    Article  Google Scholar 

  • Laska J, Davenport M, Baraniuk R (2009) Exact signal recovery from sparsely corrupted measurements through the pursuit of justice. In: Asilomar Conference on Signals, Systems and Computers, IEEE, pp 1556–1560

    Google Scholar 

  • Lei J, Yang J, Wang J, Yang Z (2009) A robust voice activity detection algorithm in nonstationary noise. In: International Conference on Industrial and Information Systems, IEEE, pp 195 – 198.

    Google Scholar 

  • Logan (1965) Properties of high-pass signals. Ph.D. thesis, Clumbia University.

    Google Scholar 

  • Lopez R, Boulgouris N (2010) Compressive sensing and combinatorial algorithms for image compression. A project report, King’s College, London

    Google Scholar 

  • Min L, McAllister H, Black N, Adrian T (2001) Perceptual time frequency subtraction algorithm for noise reduction in hearing adis. IEEE Trans Biomed Eng 48(9):879–988

    Google Scholar 

  • Needell D (2009) Topics in compressed sensing. Ph.D. thesis, University of California

    Google Scholar 

  • Rabiner L, Schafer R (1978) Digital processing of speech signals. Prentice-Hall, Englewood Cliffs

    Google Scholar 

  • Thanki R, Kothari A (2016) Digital watermarking—technical art of hiding a message. Intell Anal Multimed Inf:426–460

    Google Scholar 

  • Thomas Q (2006) Discrete – time speech signal processing principle and practice. Pearson Education Signal Processing Series, First Indian Reprint.

    Google Scholar 

  • Tropp J, Gilbert A (2007) Signal recovery from random measurements via orthogonal matching pursuit. IEEE Trans Inf Theory 53(12):4655–4666

    Article  MATH  MathSciNet  Google Scholar 

  • Wolfgang R, Podilchuk C (1999) Perceptual watermarks for digital images and video. Proc IEEE 87(7):1277–1281

    Article  Google Scholar 

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Author information

Authors and Affiliations

  1. C. U. Shah University, Wadhwan City, Gujarat, India

    Rohit Thanki

  2. Electronics & Communication Engineering Department, Atmiya Institute of Technology and Science, Rajkot, Gujarat, India

    Komal Borisagar

  3. Electronics & Communication Engineering Department, K.S. Institute of Technology, Bengaluru, Karnataka, India

    Surekha Borra

Authors
  1. Rohit Thanki
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  2. Komal Borisagar
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  3. Surekha Borra
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Thanki, R., Borisagar, K., Borra, S. (2018). Introduction. In: Advance Compression and Watermarking Technique for Speech Signals. SpringerBriefs in Electrical and Computer Engineering(). Springer, Cham. https://doi.org/10.1007/978-3-319-69069-8_1

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  • DOI: https://doi.org/10.1007/978-3-319-69069-8_1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-69068-1

  • Online ISBN: 978-3-319-69069-8

  • eBook Packages: EngineeringEngineering (R0)

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